WO2025074138A1

WO2025074138A1 - System and method for energy and carbon aware traffic routing for applications in mobile edge cloud networks

Info

Publication number: WO2025074138A1
Application number: PCT/IB2023/059878
Authority: WO
Inventors: Selome Kostentinos TESFATSION; Xuejun Cai; Arif Ahmed; Jinhua Feng
Original assignee: Telefonaktiebolaget LM Ericsson AB
Current assignee: Telefonaktiebolaget LM Ericsson AB
Priority date: 2023-10-02
Filing date: 2023-10-02
Publication date: 2025-04-10
Anticipated expiration: 2026-04-02

Abstract

A system including a wireless device (WD), a mobile network, and an edge cloud network is described. One or more of one or more first servers and the one or more second servers are configured to perform a method including determining an end to end (E2E) service performance metric, determining an E2E energy efficiency metric and an E2E carbon efficiency metric, and determining a network path usable to provide the service. The network path maximizes the E2E energy efficiency metric and the E2E carbon efficiency metric, and meets or exceeds the E2E service performance metric. The determining of the network path includes selecting the network path that has the greatest E2E energy efficiency metric and the greatest E2E carbon efficiency metric. The one or more first servers and the one or more second servers are caused to provide the service using the network path.

Description

SYSTEM AND METHOD FOR ENERGY AND CARBON AWARE TRAFFIC ROUTING FOR APPLICATIONS IN MOBILE EDGE CLOUD NETWORKS TECHNICAL FIELD The present disclosure relates to wireless communications, and in particular, to traffic routing associated with software applications in mobile edge cloud networks. BACKGROUND The Third Generation Partnership Project (3GPP) has developed and is developing standards for Fourth Generation (4G) (also referred to as Long Term Evolution (LTE)), Fifth Generation (5G) (also referred to as New Radio (NR)), Sixth Generation (6G) wireless communication systems. Such systems provide, among other features, broadband communication between network nodes, such as base stations, and mobile wireless devices (WD) (e.g., user equipment (UE), as well as communication between network nodes (NNs) and between WDs, via networks such as mobile networks (e.g., radio access network (RAN), core network, etc.), edge cloud networks, etc. Some software applications (e.g., such those related to augmented reality (AR), virtual reality (VR), Internet of Things (IoT), self-driving cars, gaming, edge applications, etc.) may be deployed in an in the edge cloud network (e.g., in order to improve the performance of the software applications). More specifically, edge applications may include an edge application client running on the WD (connected to the mobile network) and an edge application server. Further, edge sites can be distributed in a wide area mobile network, e.g., 5G, to provide services to mobile users. In addition, some software applications have moved from being monolithic applications to services (or providing services) comprising microservices with complex dependencies. For example, microservices may depend from various entities throughout various networks. That is, to provide the microservices an execution path associated with the various networks may be used. The execution path, which may be referred to as service chain, may be the connection of an ordered list of microservices forming a complete end-to-end service through which traffic or requests are directed. Some microservices can be part of multiple request execution paths or microservice chains simultaneously which can complicate the interaction pattern among microservices. The microservice instances belonging to a service chain may be deployed in a distributed manner, e.g., in different edge clusters based on the requirements associated to these microservices, resource limitation in each edge cluster, etc. Further, traffic routing may take place over a distributed execution environment comprising multiple clusters. These environments can be heterogenous in terms of available capacity, capability to handle service load, performance, energy usage, etc. FIG. 1 shows an example system (e.g., a mobile edge cloud) including multiple distributed and micro edge sites and/or data centers (DCs) for an example 5G network scenario. The edge sites may be connected to the core network through the User Plane Function (UPF). One edge site can be connected directly to multiple UPFs and, and one UPF can also be connected directly to multiple edge sites. In addition, one edge site can communicate with other edge sites, and the UPF can also communicate with other UPFs. Edge Application Server component, which may be referred to as the edge service, may include multiple microservices which can be deployed into different clusters/edge sites. Each microservice can have replicates in more than one edge sites. When the end users send request to a backend edge service, the mobile network first sets up the data plane path between the WDs and the UPF according to some requirements. For example, the network control plane can apply policies for attaching a client to UPFs based on location. A proper edge service instance running in an edge site has to also be discovered to serve a request sent by an application client on the WD. The selection of edge sites and routing from the UPF to the edge site is typically handled via domain name system (DNS). Update of DNS entries can be allowed to select the edge site and control the routing from the UPF to the edge (i.e., edge cloud network). The DNS server could select a proper edge service instance by considering the network connection between the UPFs and corresponding edge/cloud sites. Service selection may refer to the selection of the frontend or ingress microservice of the requested edge service. Once the request is forwarded to the ingress gateway in the selected edge site, the traffic paths need to be determined, i.e., the set of microservice instances through which the traffic is to be forwarded to fulfill constraints such as performance, cost, etc. In this regard, the problem of routing traffic in an optimized way becomes more complex, particularly when considering the end-to-end path covering the mobile network and edge cloud and also in the case of dealing with microservice-based applications distributed across geographical areas. Further, many applications are subject to performance fluctuations due to conditions such as hardware capacity and capability, geographical distance between the source and destination nodes, underlying network condition, etc. For performance metric latency, for example, its estimation may be dependent on the latency between the source and destination node (WD to UPF and to edge site), service queuing latency, service processing latency, and cross-cluster latency between edge sites if microservices instances are distributed across sites. In this regard, traffic routing optimization may involve directing traffic from the source towards an (or a set of) optimal destination endpoint(s) to fulfill performance requirements. In addition, it has become important to consider energy sustainability in the management and operations of services. In general, energy sustainability may cover two main aspects, energy efficiency and carbon efficiency. Carbon efficiency approaches aim to reduce greenhouse gas (GHG) (e.g., carbon dioxide (CO2)) emissions, for example, through the use of electricity generated by renewable energy sources and/or through the use of low-carbon grid energy. The emissions from the use of electricity may be referred to as scope 2 emissions. Scope 1- direct emissions and scope 3-emobodied emissions are also other emission types. Further, two metrics for carbon efficiency are emission rate in terms of grams of CO2 per second (g.CO2 per sec) and carbon intensity in terms of grams of CO2 per kilowatt-hour (g.CO2/KWH). Some existing systems may provide application visibility into their own carbon usage, e.g., a virtualization layer that provides an abstraction of the physical energy system and exposes software defined application level carbon usage which can be used for further optimization. Energy efficiency approaches aim to reduce the energy usage when performing a given task. The task performed can be in terms of data volume, number of requests/transactions, latency, etc. Over the years, energy consumption has become an important concern in the management of systems due to issues associated with high cost, increased interest from service providers, regulators, etc. Measurement of energy consumption of cloud native applications that run in a shared environment could be done based software-based estimation methods. Many existing estimation technology rely on the running average power limit (RAPL) provided by processor vendors, hardware events and/or other metrics to calculate energy consumption. However, accuracy can be impacted by the metrics collection and the used model. Further, considering the end-to-end energy consumption and carbon emission related to edge services, energy and the carbon footprint are attributed from a device, edge cloud infrastructure for hosting and running the service, and in the mobile network, typically while accessing the edge service from a mobile/5G connectivity. As shown in FIG. 1, if one service (e.g., the ingress microservices) is deployed into different edge sites (e.g., the first edge site and the second edge site), the traffic from the end users in the same radio network could go through different network paths (e.g., from the base station (BS) through the UPF to the edge site, i.e., BS-UPF-Edge site) as well as the different paths in the edge cloud network if the dependent microservices are distributed across sites (e.g., microservice in both of the second edge site and the third site). For the latter case, the traffic could go through different paths (e.g., edge site 1-edge site 2 or edge site 1 to edge site 3). Hence, the end-to-end energy consumption and carbon emission may be different (e.g., depending on the path) for the traffic from the same end user. Some existing technologies aim to load balance traffic based on quality of service (QoS) and energy consumption by performing location-aware traffic scheduling. For example, an energy-efficient service scheduling algorithm in federated edge cloud may be used to try to minimize energy consumption on the service path and try to maintain QoS at the same time. However, the service path is reconfigured when the central processing unit (CPU) utilization of any edge server exceeds beyond the predefined target. Other existing technology may distribute requests based on the carbon footprint along the traffic paths. For example, a low-carbon workload scheduling policy may be used in a Kubernetes cluster. For a cluster for which nodes span over multiple global regions, the scheduling policy selects the compute nodes to host the containers based on the real-time carbon intensity of the electric grid in the region they are in. However, only the carbon emission during the workload placement or scheduling is considered, not the traffic optimization during the operation of the service. Further, a wait-and-scale strategy may be employed, where the execution of an application is suspended when the grid power intensity increases above a given threshold and scale up resources for an application when carbon emissions are below the threshold. In addition, carbon aware routing process may be performed, based on contributing elements, where the routing process tries to route traffic along network paths that minimize the carbon footprint. However, the impact of only a single network is considered, and energy efficiency in the decision making is not taken into account. Further, energy efficiency and carbon efficiency may be correlated (e.g., less carbon emission due to lower energy consumption of a facility powered by non-renewable energy source). However, efficiency in one does not necessarily mean efficiency in another. For example, the most energy-efficient system can be greatly carbon-inefficient if powered by fossil-based energy sources. Conversely, the most carbon-efficient system can be greatly energy-inefficient due to sub-optimal usage of energy, attributed for example in the poor design and operation of a facility. In sum, existing technology may take into account the energy efficiency or carbon emission in one domain, e.g., the edge cloud, but ignores information about other domains to select network paths. SUMMARY Some embodiments advantageously provide methods, systems, and apparatuses for routing of traffic associated with communication between one or more devices (e.g., network nodes, servers, wireless devices). In some embodiments, the traffic routing is energy-and-carbon aware for software applications (e.g., in mobile edge cloud networks). One or more embodiments provide a method to optimize end-to-end energy and carbon efficiency of an edge service covering more than one network (e.g., the mobile network and the edge cloud network). In some embodiments, the method jointly considers service, infrastructure and topology information in the mobile network and edge cloud network for configuration of WD traffic routing that meets other requirements such as performance and sustainability requirements. In some other embodiments, the method includes interacting (or is performed via the interaction) between the mobile network and the edge cloud network. One or more embodiments provide a method that optimizes service level energy and carbon efficiency together in the mobile network and edge cloud. In some embodiments, the method considers two of the most important metrics in energy sustainability, i.e., energy and carbon efficiency. In some other embodiments, the method includes exchanging and collecting the energy and carbon efficiency information between the edge cloud and mobile network. In some embodiments, the method includes determining the carbon and energy information of service paths by analyzing the related network, edge cloud and service information (e.g., performance requirement from the service, network topology, energy and carbon information of components). In some other embodiments, the method includes optimizing the end-to-end energy and carbon efficiency of a service through optimized service traffic paths. In some embodiments, the method provides a three-step path selection such as UPF-selection, edge site selection/discovery, and microservice instance routing path. In some other embodiments, the method includes utilizing trade-off between energy and carbon efficiency if required for flexible decision making. One or more embodiments can be applied for optimizing both carbon and energy efficiency, which are important to achieve a cleaner and more energy-savings results and hence a better sustainable performance. The method may be implemented in a mobile network and edge cloud and may be useful for a holistic management across multiple layers. Further, the method may provide optimization for fine-grained management at service-request level which may be important for an accurate and dependable decision making, e.g., charging and billing. According to one aspect, a system comprising a wireless device (WD), a mobile network, and an edge cloud network is described. The WD is configured to communicate with the mobile network and the edge cloud network. The mobile network includes one or more first servers. The edge cloud network includes one or more second servers. One or more of the one or more first servers and the one or more second servers are configured to perform steps of a method. The method includes determining an end to end (E2E) service performance metric corresponding to a service provided to the WD by the mobile network and the edge cloud network, determining an E2E energy efficiency metric and an E2E carbon efficiency metric corresponding to the service provided to the WD by the mobile network and the edge cloud network, and determining a network path. The network path includes a mobile network path and an edge cloud network path usable by the mobile network and the edge cloud network, respectively, to provide the service. The network path maximizes the E2E energy efficiency metric and the E2E carbon efficiency metric. The network path meets or exceeds the E2E service performance metric. The determining of the network path includes selecting the network path from a plurality of network paths. The selected network path has the greatest E2E energy efficiency metric and the greatest E2E carbon efficiency metric of each one of the plurality of network paths. The method also includes causing the one or more first servers and the one or more second servers to provide the service using the network path. According to another aspect, a method in a first network node in a mobile network is described. The first network node is configured to communicate with a second network node in an edge cloud network. The method includes obtaining, for each one of a plurality of mobile network components, an E2E energy efficiency metric and an E2E carbon efficiency metric corresponding to a service provided to the WD at least by the mobile network and determining a mobile network path usable by the mobile network to provide the service. The mobile network path is part of a network path usable by the mobile network and the edge cloud network to provide the service. The mobile network path is determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric. The method further includes transmitting information associated with the mobile network path to the second network node. In some embodiments, the method further includes selecting a user plane function (UPF) based on the determined mobile network path. In some other embodiments, the method further includes obtaining information corresponding to network routing from the selected UPF to the edge cloud network. In some embodiments, the method further includes updating a policy and changing the network routing for service requests based on the selected UPF. In some other embodiments, the method further includes selecting an edge site based on the selected UPF and service information. The edge site hosts the service. The selected edge site is included in the information associated with the mobile network path. In some embodiments, the mobile network path is further based on an E2E service performance metric corresponding to the service provided to the WD by the mobile network and the edge cloud network. In some other embodiments, the E2E service performance metric is based on a first delay and a second delay. The first delay is between the WD and the edge cloud network. The first delay is associated with the service. The second delay is between the service and another service of a different edge site. In some embodiments, one or both of the E2E energy efficiency metric is based on energy usage for a data path including the mobile network and the edge cloud network, and the E2E carbon efficiency metric is based on a first carbon intensity of the data path. The first carbon intensity of the data path is based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path. In some other embodiments, the first network node comprises a network data analytics function (NWDAF). According to one aspect, a first network node in a mobile network is described. The first network node is configured to communicate with a second network node in an edge cloud network and configured to perform any one of steps corresponding to the method in a first network node. According to another aspect, a method in a second network node in an edge cloud network is described. The second network node is configured to communicate with a first network node in a mobile network and a wireless device (WD). The method includes receiving, from the first network node, information associated with a mobile network path usable at least by the mobile network to provide a service to the WD, obtaining, for each one of a plurality of edge cloud network components, an end to end (E2E) energy efficiency metric and an E2E carbon efficiency metric corresponding to the service provided to the WD at least by the edge cloud network, and determining an edge cloud network path usable by the edge cloud network to provide the service. The edge cloud network path is determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric. The method further includes determining a network path usable by the mobile network and the edge cloud network to provide the service. The network path includes the mobile network path and the edge cloud network path. The network path is determined based on the information associated with the mobile network path, the edge cloud network path, the E2E energy efficiency metric, and the E2E carbon efficiency metric The method also includes causing one or more edge cloud network components of the plurality of edge cloud network components to provide the service using the network path. In some embodiments, the method further includes receiving, from the WD, a service request corresponding to the service. The service request is based on a domain name system (DNS) response provided by the first network node. The DNS response includes an external address of an ingress gateway associated with an edge site of the edge cloud network. In some other embodiments, the method further includes selecting the edge cloud network path based on service instances connected to the ingress gateway and other service instances depending on at least one other service instance across edge sites. The selected cloud edge network path is usable to determine the network path. In some embodiments, the method further includes determining a network path selection policy for the configuration of the network path based at least on the E2E energy efficiency metric and the E2E carbon efficiency metric. In some other embodiments, determining the edge cloud network path is further based on an E2E service performance metric corresponding to the service provided to the WD by the mobile network and the edge cloud network. In some embodiments, the E2E service performance metric is based on a first delay and a second delay. The first delay is between the WD and the edge cloud network. The first delay is associated with the service. The second delay is between the service and another service of a different edge site. In some other embodiments, one or both of the E2E energy efficiency metric is based on energy usage for a data path including the mobile network and the edge cloud network, and the E2E carbon efficiency metric includes a first carbon intensity of the data path. The first carbon intensity of the data path is based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path. In some embodiments, the method further includes applying the network path using routing path header injection. In some other embodiments, the method further includes subscribing to the first network node to receive the information associated with the mobile network path. The information includes events related to selection of the mobile network path. In some other embodiments, the information associated with the mobile network path includes edge site information. In some other embodiments, one or both of the service is a microservice and the one or more components include one or more servers. According to one aspect, a second network node in an edge cloud network is described. The second network node is configured to communicate with a first network node in a mobile network and a wireless device (WD). The second network is configured to perform one or more steps corresponding to the method in the second network node. BRIEF DESCRIPTION OF THE DRAWINGS A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein: FIG. 1 shows a high-level overview of an example system; FIG. 2 is a schematic diagram of an example network architecture illustrating a communication system connected via an intermediate network to a host computer according to the principles in the present disclosure; FIG. 3 is a block diagram of a host computer communicating via a network node with a wireless device over an at least partially wireless connection according to some embodiments of the present disclosure; FIG. 4 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for executing a client application at a wireless device according to some embodiments of the present disclosure; FIG. 5 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a wireless device according to some embodiments of the present disclosure; FIG. 6 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data from the wireless device at a host computer according to some embodiments of the present disclosure; FIG. 7 is a flowchart illustrating example methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a host computer according to some embodiments of the present disclosure; FIG. 8 is a flowchart of an example process in a network node according to some embodiments of the present disclosure; FIG. 9 is a flowchart of an example process in another network node according to some embodiments of the present disclosure; FIG. 10 shows an example of the gaps of some technologies according to some embodiments of the present disclosure; FIG. 11 is a flowchart of an example process according to some embodiments of the present disclosure; FIG. 12 shows an example mobile and cloud edge network components according to some embodiments of the present disclosure; FIG. 13 shows an example implementation of the network components according to some embodiments of the present disclosure; FIG. 14 shows steps of an example process according to some embodiments of the present disclosure; and FIG. 15 shows other steps of the example process according to some embodiments of the present disclosure. DETAILED DESCRIPTION Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to routing of traffic associated with communication between one or more devices (e.g., network nodes, servers, wireless devices). Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Like numbers refer to like elements throughout the description. As used herein, relational terms, such as “first” and “second,” “top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. In embodiments described herein, the joining term, “in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate, and modifications and variations are possible of achieving the electrical and data communication. In some embodiments described herein, the term “coupled,” “connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and/or wireless connections. The term “network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multi- standard radio (MSR) radio node such as MSR BS, multi-cell/multicast coordination entity (MCE), integrated access and backhaul (IAB) node, relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, RAN components, one or more Kubernetes (K8s) components, access and mobility management function (AMF), session management function (SMF), an element manager (EM), network data analytic function (NWDAF), operations, administration and management (OAM), network exposure function (NEF), edge management system, edge application framework, user plane function (UPF), domain name server (DNS), control plane (CP) network functions, user plane network functions, DNS resolver, ingress gateway, etc. The network node may also comprise a mobile network (MN) edge cloud monitor, an MN data manager, MN traffic routing manager, UPF selector, edge service selector, MN exposure, edge cloud (EC) data manager, EC traffic routing manager, EC monitor, EC exposure, microservice instances selector, test equipment, etc. The term “radio node” used herein may be used to also denote a wireless device (WD) such as a wireless device (WD) or a radio network node. In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) or mobile device are used interchangeably. The WD herein can be any type of wireless device capable of communicating with a network node or another WD over radio signals, such as wireless device (WD). The WD may also be a radio communication device, target device, device to device (D2D) WD, machine type WD or WD capable of machine to machine communication (M2M), low-cost and/or low- complexity WD, a sensor equipped with WD, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (IoT) device, or a Narrowband IoT (NB-IOT) device, a wearable device, etc. Also, in some embodiments the generic term “radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell/multicast Coordination Entity (MCE), IAB node, relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH). Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and/or New Radio (NR), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure. Note further, that functions described herein as being performed by a wireless device or a network node may be distributed over a plurality of wireless devices and/or network nodes. In other words, it is contemplated that the functions of the network node and wireless device described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Referring again to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 2 a schematic diagram of a communication system 10, according to an embodiment, such as a 3GPP-type cellular network that may support standards such as LTE and/or NR (5G), which comprises an access network 12, such as a radio access network, and/or a transport network 13, and/or a core network 14, and/or an edge cloud network 15. One or more of access network 12, transport network 13, and core network 14 may be comprised in a mobile network. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c, such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the transport network 13 over a wired or wireless connection 20 (or any other connection), to the core network 14 via wired or wireless connection 21 (or any other connection), and to the edge cloud network 15 via wired or wireless connection 23. Transport network 13 may include one or more network nodes 16 such as network node 16d. Transport network 13 may be referred to as a data network. Core network 14 may include one or more network nodes 16 such as network node 16e. Edge cloud network 15 may include one or more network nodes such as network node 16f. Network nodes 16a, 16b, 16c, 16d, 16e, 16f may be referred to collectively as network nodes 16. It is noted that network nodes 16 shown in particular networks, e.g., network node 16f in edge cloud network 15, is done merely for ease of understanding that a network node 16 can be withing a particular network type, e.g., edge cloud network, and not to imply that a specific network node 16f can only be in edge cloud network 15. Different network nodes, e.g., network node 16b, can be located in networks other than those shown in FIG. 2. For example, network node 16b can be located in an edge cloud network 15. Further, transport network node 13 may be configured to connect (e.g., via wired or wireless connection) directly/indirectly to edge cloud network 15, and edge cloud network 15 may be configured to connect (e.g., via wired or wireless connection) directly/indirectly to any network node 16. Core network 14 may also be configured to directly connect (e.g., via wired or wireless connection) directly/indirectly to any network node 16. A first wireless device (WD) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16a. A second WD 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16b. While a plurality of WDs 22a, 22b (collectively referred to as wireless devices 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole WD is in the coverage area or where a sole WD is connecting to the corresponding network node 16. Note that although only two WDs 22 and six network nodes 16 are shown for convenience, the communication system may include many more WDs 22 and network nodes 16. Any WD 22 may be configured to connect (e.g., via wired or wireless connection) directly/indirectly to any network such as access network 12, transport network 13, core network 14, and edge cloud network 15. Also, it is contemplated that a WD 22 can be in simultaneous communication and/or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a WD 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, WD 22 can be in communication with an eNB for LTE/E-UTRAN and a gNB for NR/NG-RAN. Further, although not shown in FIG. 2, WDs 22 may communicate directly with any of the network nodes 16d, 16e, 16f. Similarly, network nodes 16a, 16b, 16c may communicate directly with network nodes 16e, 16f. The communication system 10 may itself be connected to a host computer 24, which may be embodied in the hardware and/or software of a standalone server, a cloud- implemented server, a distributed server or as processing resources in a server farm. The host computer 24 may be under the ownership or control of a service provider, or may be operated by the service provider or on behalf of the service provider. The connections 26, 28 between the communication system 10 and the host computer 24 may extend directly from the core network 14 to the host computer 24 or may extend via an optional intermediate network 30. The intermediate network 30 may be one of, or a combination of more than one of, a public, private or hosted network. The intermediate network 30, if any, may be a backbone network or the Internet. In some embodiments, the intermediate network 30 may comprise two or more sub-networks (not shown). The communication system of FIG. 2 as a whole enables connectivity between one of the connected WDs 22a, 22b and the host computer 24. The connectivity may be described as an over-the-top (OTT) connection. The host computer 24 and the connected WDs 22a, 22b are configured to communicate data and/or signaling via the OTT connection, using the access network 12, the core network 14, any intermediate network 30 and possible further infrastructure (not shown) as intermediaries. The OTT connection may be transparent in the sense that at least some of the participating communication devices through which the OTT connection passes are unaware of routing of uplink and downlink communications. For example, a network node 16 may not or need not be informed about the past routing of an incoming downlink communication with data originating from a host computer 24 to be forwarded (e.g., handed over) to a connected WD 22a. Similarly, the network node 16 need not be aware of the future routing of an outgoing uplink communication originating from the WD 22a towards the host computer 24. A network node 16 is configured to include a NN management unit 32 which is configured to perform any step and/or task and/or process and/or method and/or feature described in the present disclosure, e.g., NN functions, server functions, edge server functions, etc. A wireless device 22 is configured to include a WD management unit 34 which is configured to perform any step and/or task and/or process and/or method and/or feature described in the present disclosure, e.g., WD functions. Example implementations, in accordance with an embodiment, of the WD 22, network node 16 and host computer 24 discussed in the preceding paragraphs will now be described with reference to FIG. 3. In a communication system 10, a host computer 24 comprises hardware (HW) 38 including a communication interface 40 configured to set up and maintain a wired or wireless connection with an interface of a different communication device of the communication system 10. The host computer 24 further comprises processing circuitry 42, which may have storage and/or processing capabilities. The processing circuitry 42 may include a processor 44 and memory 46. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 42 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 44 may be configured to access (e.g., write to and/or read from) memory 46, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory). Processing circuitry 42 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by host computer 24. Processor 44 corresponds to one or more processors 44 for performing host computer 24 functions described herein. The host computer 24 includes memory 46 that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 48 and/or the host application 50 may include instructions that, when executed by the processor 44 and/or processing circuitry 42, causes the processor 44 and/or processing circuitry 42 to perform the processes described herein with respect to host computer 24. The instructions may be software associated with the host computer 24. The software 48 may be executable by the processing circuitry 42. The software 48 includes a host application 50. The host application 50 may be operable to provide a service to a remote user, such as a WD 22 connecting via an OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the remote user, the host application 50 may provide user data which is transmitted using the OTT connection 52. The “user data” may be data and information described herein as implementing the described functionality. In one embodiment, the host computer 24 may be configured for providing control and functionality to a service provider and may be operated by the service provider or on behalf of the service provider. The processing circuitry 42 of the host computer 24 may enable the host computer 24 to observe, monitor, control, transmit to and/or receive from the network node 16 and or the wireless device 22. The processing circuitry 42 of the host computer 24 may include a host management unit 54 configured to enable the service provider to observe, monitor, control, transmit to/receive from the network node 16 and or the wireless device 22. The communication system 10 further includes a network node 16 provided in a communication system 10 and including hardware 58 enabling it to communicate with the host computer 24 and with the WD 22. Network node 16 may include server 17 configured to perform any of the network node functions described herein. Further, network node 16 may be referred to as server 17. The hardware 58 may include a communication interface 60 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 10, as well as a radio interface 62 for setting up and maintaining at least a wireless connection 64 with a WD 22 located in a coverage area 18 served by the network node 16. The radio interface 62 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers. The communication interface 60 may be configured to facilitate a connection 66 to the host computer 24. The connection 66 may be direct or it may pass through a core network 14 of the communication system 10 and/or through one or more intermediate networks 30 outside the communication system 10. In the embodiment shown, the hardware 58 of the network node 16 further includes processing circuitry 68. The processing circuitry 68 may include a processor 70 and a memory 72. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 68 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 70 may be configured to access (e.g., write to and/or read from) the memory 72, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory). Thus, the network node 16 further has software 74 stored internally in, for example, memory 72, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. Software 74 may include NN application 75 (e.g., a software application, a software component/task, etc.). The software 74 may be executable by the processing circuitry 68. The processing circuitry 68 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by network node 16. Processor 70 corresponds to one or more processors 70 for performing network node 16 functions described herein. The memory 72 is confi30gured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 74 may include instructions that, when executed by the processor 70 and/or processing circuitry 68, causes the processor 70 and/or processing circuitry 68 to perform the processes described herein with respect to network node 16. For example, processing circuitry 68 of the network node 16 may a NN management unit 32 which is configured to perform any step and/or task and/or process and/or method and/or feature described in the present disclosure. For example, NN management unit 32 may be configured to perform monitoring functions, data manager functions, routing manager functions, edge service selector functions, UPF selector functions, exposure functions, traffic routing manager functions, microservice instances selector functions, EM functions, Network Data Analytics Function (NWDAF), OAM functions, NEF functions, edge management system functions, edge application framework functions, which may be performed by one or more hardware (and/or software) units included in NN management unit 32 (and/or NN 16). The communication system 10 further includes the WD 22 already referred to. The WD 22 may have hardware 80 that may include a radio interface 82 configured to set up and maintain a wireless connection 64 with a network node 16 serving a coverage area 18 in which the WD 22 is currently located. The radio interface 82 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers. The hardware 80 of the WD 22 further includes processing circuitry 84. The processing circuitry 84 may include a processor 86 and memory 88. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 84 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 86 may be configured to access (e.g., write to and/or read from) memory 88, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory). Thus, the WD 22 may further comprise software 90, which is stored in, for example, memory 88 at the WD 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the WD 22. The software 90 may be executable by the processing circuitry 84. The software 90 may include a WD application 92 (e.g., a software application, a software component/task, mobile application, a client application, etc.). The WD application 92 may be operable to provide a service to a human or non-human user via the WD 22, with the support of the host computer 24. In the host computer 24, an executing host application 50 may communicate with the executing WD application 92 via the OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the user, the WD application 92 may receive request data from the host application 50 and provide user data in response to the request data. The OTT connection 52 may transfer both the request data and the user data. The WD application 92 may interact with the user to generate the user data that it provides. The processing circuitry 84 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by WD 22. The processor 86 corresponds to one or more processors 86 for performing WD 22 functions described herein. The WD 22 includes memory 88 that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 90 and/or the WD application 92 may include instructions that, when executed by the processor 86 and/or processing circuitry 84, causes the processor 86 and/or processing circuitry 84 to perform the processes described herein with respect to WD 22. For example, the processing circuitry 84 of the wireless device 22 may include a WD management unit 34 which is configured to perform any step and/or task and/or process and/or method and/or feature described in the present disclosure. For example, WD management unit 34 may be configured to perform offload controller functions, device monitor functions, and software application functions, any of which may be performed by one or more hardware (and/or software) units included in WD management unit 34 (and/or WD 22). In some embodiments, the inner workings of the network node 16, WD 22, and host computer 24 may be as shown in FIG. 3 and independently, the surrounding network topology may be that of FIG. 2. In FIG. 3, the OTT connection 52 has been drawn abstractly to illustrate the communication between the host computer 24 and the wireless device 22 via the network node 16, without explicit reference to any intermediary devices and the precise routing of messages via these devices. Network infrastructure may determine the routing, which it may be configured to hide from the WD 22 or from the service provider operating the host computer 24, or both. While the OTT connection 52 is active, the network infrastructure may further take decisions by which it dynamically changes the routing (e.g., on the basis of load balancing consideration or reconfiguration of the network). The wireless connection 64 between the WD 22 and the network node 16 is in accordance with the teachings of the embodiments described throughout this disclosure. One or more of the various embodiments improve the performance of OTT services provided to the WD 22 using the OTT connection 52, in which the wireless connection 64 may form the last segment. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and/or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc. In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 52 between the host computer 24 and WD 22, in response to variations in the measurement results. The measurement procedure and/or the network functionality for reconfiguring the OTT connection 52 may be implemented in the software 48 of the host computer 24 or in the software 90 of the WD 22, or both. In embodiments, sensors (not shown) may be deployed in or in association with communication devices through which the OTT connection 52 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or supplying values of other physical quantities from which software 48, 90 may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 52 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not affect the network node 16, and it may be unknown or imperceptible to the network node 16. Some such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary WD signaling facilitating the host computer’s 24 measurements of throughput, propagation times, latency and the like. In some embodiments, the measurements may be implemented in that the software 48, 90 causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 52 while it monitors propagation times, errors, etc. Thus, in some embodiments, the host computer 24 includes processing circuitry 42 configured to provide user data and a communication interface 40 that is configured to forward the user data to a cellular network for transmission to the WD 22. In some embodiments, the cellular network also includes the network node 16 with a radio interface 62. In some embodiments, the network node 16 is configured to, and/or the network node’s 16 processing circuitry 68 is configured to perform the functions and/or methods described herein for preparing/initiating/maintaining/supporting/ending a transmission to the WD 22, and/or preparing/terminating/maintaining/supporting/ending in receipt of a transmission from the WD 22. In some embodiments, the host computer 24 includes processing circuitry 42 and a communication interface 40 that is configured to a communication interface 40 configured to receive user data originating from a transmission from a WD 22 to a network node 16. In some embodiments, the WD 22 is configured to, and/or comprises a radio interface 82 and/or processing circuitry 84 configured to perform the functions and/or methods described herein for preparing/initiating/maintaining/supporting/ending a transmission to the network node 16, and/or preparing/terminating/maintaining/supporting/ending in receipt of a transmission from the network node 16. Although FIGS. 2 and 3 show various “units” such as NN management unit 32, and WD management unit 34 as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry. FIG. 4 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIGS. 2 and 3, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIG. 3. In a first step of the method, the host computer 24 provides user data (Block S100). In an optional substep of the first step, the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50 (Block S102). In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block S104). In an optional third step, the network node 16 transmits to the WD 22 the user data which was carried in the transmission that the host computer 24 initiated, in accordance with the teachings of the embodiments described throughout this disclosure (Block S106). In an optional fourth step, the WD 22 executes a client application, such as, for example, the WD application 92, associated with the host application 50 executed by the host computer 24 (Block S108). FIG. 5 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 2, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 2 and 3. In a first step of the method, the host computer 24 provides user data (Block S110). In an optional substep (not shown) the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50. In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block S112). The transmission may pass via the network node 16, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional third step, the WD 22 receives the user data carried in the transmission (Block S114). FIG. 6 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 2, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 2 and 3. In an optional first step of the method, the WD 22 receives input data provided by the host computer 24 (Block S116). In an optional substep of the first step, the WD 22 executes the WD application 92, which provides the user data in reaction to the received input data provided by the host computer 24 (Block S118). Additionally or alternatively, in an optional second step, the WD 22 provides user data (Block S120). In an optional substep of the second step, the WD provides the user data by executing a client application, such as, for example, WD application 92 (Block S122). In providing the user data, the executed WD application 92 may further consider user input received from the user. Regardless of the specific manner in which the user data was provided, the WD 22 may initiate, in an optional third substep, transmission of the user data to the host computer 24 (Block S124). In a fourth step of the method, the host computer 24 receives the user data transmitted from the WD 22, in accordance with the teachings of the embodiments described throughout this disclosure (Block S126). FIG. 7 is a flowchart illustrating an example method implemented in a communication system, such as, for example, the communication system of FIG. 2, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 2 and 3. In an optional first step of the method, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 16 receives user data from the WD 22 (Block S128). In an optional second step, the network node 16 initiates transmission of the received user data to the host computer 24 (Block S130). In a third step, the host computer 24 receives the user data carried in the transmission initiated by the network node 16 (Block S132). FIG. 8 is a flowchart of an example process (i.e., method) in a network node 16 (i.e., first network node 16). One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 68 (including the NN management unit 32), processor 70, radio interface 62 and/or communication interface 60. Network node 16 such as via processing circuitry 68 and/or processor 70 and/or radio interface 62 and/or communication interface 60 is configured to obtain (Block S134), for each one of a plurality of mobile network components, an E2E energy efficiency metric and an E2E carbon efficiency metric corresponding to a service provided to the WD 22 at least by the mobile network 100. The network node 16 is further configured to determine (Block S136) a mobile network path usable by the mobile network 100 to provide the service. The mobile network path is part of a network path usable by the mobile network 100 and the edge cloud network 15 to provide the service. The mobile network path is determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric. The network node 16 is further configured to transmit (Block S138) information associated with the mobile network path to the second network node 16. In some embodiments, the method further includes selecting a user plane function (UPF) based on the determined mobile network path. In some other embodiments, the method further includes obtaining information corresponding to network routing from the selected UPF to the edge cloud network 15. In some embodiments, the method further includes updating a policy and changing the network routing for service requests based on the selected UPF. In some other embodiments, the method further includes selecting an edge site 116 based on the selected UPF and service information. The edge site 116 hosts the service, and the selected edge site 116 is included in the information associated with the mobile network path. In some embodiments, the mobile network path is further based on an E2E service performance metric corresponding to the service provided to the WD 22 by the mobile network 100 and the edge cloud network 15. In some other embodiments, the E2E service performance metric is based on a first delay and a second delay. The first delay is between the WD 22 and the edge cloud network 15. The first delay is associated with the service. The second delay is between the service and another service of a different edge site 116. In some embodiments, one or both of the E2E energy efficiency metric is based on energy usage for a data path including the mobile network 100 and the edge cloud network 15, and the E2E carbon efficiency metric is based on a first carbon intensity of the data path. The first carbon intensity of the data path is based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path. In some other embodiments, the first network node 16 comprises a network data analytics function (NWDAF). FIG. 9 is a flowchart of an example process (i.e., method) in a network node 16 (i.e., second network node 16). One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 68 (including the NN management unit 32), processor 70, radio interface 62 and/or communication interface 60. Network node 16 such as via processing circuitry 68 and/or processor 70 and/or radio interface 62 and/or communication interface 60 is configured to receive (Block S140), from the first network node 16, information associated with a mobile network path, the mobile network path being usable at least by the mobile network 100 to provide a service to the WD22 and obtain (Block S142), for each one of a plurality of edge cloud network components, an end to end (E2E) energy efficiency metric and an E2E carbon efficiency metric corresponding to the service provided to the WD 22 at least by the edge cloud network 15. The network node 16 is further configured to determine (Block S144) an edge cloud network path usable by the edge cloud network 15 to provide the service. The edge cloud network path is determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric. Further, the network node 16 is further configured to determine (Block S146) a network path usable by the mobile network 100 and the edge cloud network 15 to provide the service. The network path includes the mobile network path and the edge cloud network path. The network path is determined based on the information associated with the mobile network path, the edge cloud network path, the E2E energy efficiency metric, and the E2E carbon efficiency metric. In addition, the network node 16 is configured to cause (Block S148) one or more edge cloud network components of the plurality of edge cloud network components to provide the service using the network path. In some embodiments, the method further includes receiving, from the WD 22, a service request corresponding to the service. The service request is based on a domain name system (DNS) response provided by the first network node 16. The DNS response includes an external address of an ingress gateway associated with an edge site of the edge cloud network 15. In some other embodiments, the method further includes selecting the edge cloud network path based on service instances connected to the ingress gateway and other service instances depending on at least one other service instance across edge sites. The selected cloud edge network path is usable to determine the network path. In some embodiments, the method further includes determining a network path selection policy for the configuration of the network path based at least on the E2E energy efficiency metric and the E2E carbon efficiency metric. In some other embodiments, determining the edge cloud network path is further based on an E2E service performance metric corresponding to the service provided to the WD by the mobile network and the edge cloud network. In some embodiments, the E2E service performance metric is based on a first delay and a second delay. The first delay is between the WD 22 and the edge cloud network 15. The first delay is associated with the service. The second delay is between the service and another service of a different edge site 116. In some other embodiments, one or both of the E2E energy efficiency metric is based on energy usage for a data path including the mobile network 100 and the edge cloud network 15, and the E2E carbon efficiency metric includes a first carbon intensity of the data path. The first carbon intensity of the data path is based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path. In some embodiments, the method further includes applying the network path using routing path header injection. In some other embodiments, the method further includes subscribing to the first network node 16 to receive the information associated with the mobile network path. The information includes events related to selection of the mobile network path. In some other embodiments, the information associated with the mobile network path includes edge site information. In some other embodiments, one or both of the service is a microservice and the one or more components include one or more servers 17. Having described the general process flow of arrangements of the disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the disclosure, the sections below provide details and examples of arrangements for routing of traffic associated with communication between one or more devices (e.g., network nodes 16, servers 17, wireless devices 22). Any one of the steps and/or features and/or functions described herein may be performed by network node 16 (and/or server 17) and/or its components and/or WD 22 and/or its components. In some embodiments, edge cloud network 15 and/or mobile network 100 may perform one or more steps and/or features and/or functions, where the steps, features, and/or functions may be performed by a network node 16 (and/or server 17) and/or its components and/or WD 22 and/or its components. FIG. 10 shows an example of the gaps of some technologies covering at least two networks (e.g., edge cloud network 15, mobile network 100), specifically for the edge service traffic routing process. In one or more embodiments, the gaps 94 is addressed by considering and optimizing both energy and carbon efficiency of the traffic paths in the mobile network 100 as well as in the edge infrastructure (i.e., edge cloud network 15) while meeting service assurance. A high-level flow chart of an example process (i.e., method) is shown in FIG. 11. The method may be performed by network node 16 (and/or server 17) and/or any of its components. The method includes, at step S200, monitoring infrastructure and service status, at step S202, subscribing to performance, energy and carbon information from the network and edge infrastructure, and at step S204, initiating service path selection. The method further includes, at step S206, extracting and exposing service-level energy and carbon information in mobile network and edge cloud network, at step S208, defining traffic routing policy, and at step S210, applying path selection according to policy. For example, service providers/operators may provide application requirements such as performance, service topology, tradeoffs between energy and carbon efficiencies when selecting traffic paths from a list of potential paths, etc. Then, the edge cloud network 15 and the mobile network 100 may need to obtain or estimate the energy and carbon efficiency of the various parts or components in their infrastructure that are potentially related to the edge service. For example, in the edge sites, the energy usage (e.g., in KWH) and carbon intensity (g.CO2/KWH) can be estimated for the running service replicate (e.g. container) according to certain models. In the mobile network 100, the energy and carbon intensity of the physical or virtual network function (NF) in which the mobile user (i.e., WD 22) can access the edge service can be estimated as well. When service routing selection operation is initiated, information (e.g., network topology, performance, carbon, and energy information) usable for the selection is obtained from the mobile network 100 and edge cloud network 15, e.g., by first subscribing to such information. The edge sites and mobile network 100 then expose such information to the traffic routing management logic responsible for the service path selection. The traffic management logic utilizes the exposed (per-hop) information from the networks and edge infrastructure to construct an end-to-end path level energy and carbon usage for the service together with other information (such as performance requirements for service assurance). Based on this information, traffic routing policy that optimizes the energy and carbon efficiency of the edge services is defined while meeting other requirements at the same time. The policy may be communicated to related NFs and/or management functions such as OAM and edge platform in the mobile network 100 and edge cloud network 15 to select routing paths accordingly. System Overview FIG. 12 shows an example of mobile and cloud edge network components (e.g., management functions) for enabling an end-to-end (E2E) energy and carbon efficiency traffic routing optimization between the client application (i.e., WD Application 92) in the WD 22 and the server side application (e.g., NN Application 75) in the edge cloud network 15. More specifically, communication system 10 may include an edge cloud network 15 and a mobile network 100 (which may include an access network 12, a transport network 13, a core network 14, etc.) configured to communicate with edge cloud network 15. Mobile network 100 may comprise MN E-C monitor 102, MN data manager 104, MN traffic routing manager 106, UPF selector 108, edge service selector 110, and MN exposure, any of which may be part of one or more network nodes 16 (e.g., network node 16a, server 17, NN management unit 32, etc.). Edge cloud network 15 may include EC data manager 122, EC traffic routing manager 114, EC E-C monitor 118, EC exposure 120, microservice instances selector 124, any of which any of which may be part of one or more network nodes 16 (e.g., network node 16b, server 17, NN management unit 32, etc.) Edge sites 116 such as edge sites 116a, 116b may include one or more of EC E-C monitor 118, EC exposure 120, microservice instances selector 124. The optimization may be performed with regard to ensuring the E2E service performance. The E2E service performance may be determined by the performance of the service both at network and edge cloud layers, and hence a Service Level Objective (SLO) targets may be specified to represent E2E performance target covering the network and cloud side requirements. The E2E SLO can be decomposed into SLOs for constituent network and edge cloud network parts. The mobile network traffic routing optimization and edge cloud network traffic routing optimization logics (i.e., functions performed by network nodes 16 corresponding to each network) may work in optimizing the energy and carbon efficiency of their environment under the constraint of the individual performance requirement and may also interact by exposing the traffic routing decisions with each other for the E2E efficiency enhancement. The Mobile Network Energy and Carbon efficiency Monitor 102 (MN E-C Monitor) may be a function (e.g., comprised in NN management unit 32) such as a logical function for measuring or estimating the energy and carbon efficiency of components such as physical network functions and virtual network functions in the mobile network 100. MN E-C Monitor 102 may be distributed on the network to monitor the different parts of the network (e.g., the base station, UPF). MN E-C Monitor 102 may also determine the performance (such as delay) in the network. MN E-C Monitor 102 can be part of other components or a separate component (e.g., of NN 16 and/or server 17) that is capable of measuring or calculating energy and carbon efficiency metric in real time. MN E-C Monitor 102 may include an interface to the MN Data Manager 104 to report the measured metrics. MN Data Manager 104 is an entity (e.g., comprised in NN management unit 32) configured to extract metrics such as energy and carbon efficiency metrics from the MN E-C Monitor 102 and aggregate the metrics such as aggregating the network performance, energy and carbon efficiency at path level. MN Data Manager 104 may use the network topology to construct paths. MN Data Manager 104 may also cache already selected paths by communicating with MN traffic routing manager 106. MN Data Manager 104 may send the pre-processed data to the MN traffic routing manager 106. MN traffic routing manager 106 may be configured for the selection of paths that can fulfill the energy and carbon efficiency as well as performance requirements. MN traffic routing manager 106 considers network conditions, network-side performance and requirement, topology of the mobile network and edge site connection, deployment status, etc. to determine a policy for mobile network path selection. The policy may be a connectivity policy consisting of RAN, user plane path traversing core network (i.e., through UPF selection) and networking between UPF and service instance/the ingress service of the microservice chain (i.e., through edge service selection). The selection may be performed dynamically for each or a batch of service requests. To minimize overhead, the MN traffic routing manager 106 may use techniques such as caching to extract the latest information about the selected UPF for a given WD 22 and its performance. MN traffic routing manager 106 may also consider the impact of other WDs 22 in the UPF selection process. In case of path (re)-selection the MN traffic routing manager 106 sends the configuration policy to the UPF selector 108 and edge service selector 110 to perform UPF (re-) selection and/or (re-) selection of edge site, respectively. UPF selector 108 interacts and triggers a network component (e.g., SMF) that performs UPF (re-) selection. The SMF also considers other conditions such as the location and network conditions in the decision making. Edge Service Selector 110 may control the routing from the UPF to edge (e.g., the DNS resolver). Edge Service Selector 110 may resolve service name (via DNS request) into external internet protocol (IP) address of one or more ingress gateways. In the edge cloud network 15, the exposed information may be communicated to the edge cloud (EC) Traffic Routing manager 114 of the selected edge site 116 that is hosting the ingress service. Monitoring and analysis may be performed to select a proper path for the request to be handled by the service chain in the edge cloud network 15. In some embodiments, EC E-C Monitor 118 may be located at every edge site 116 and be an entity responsible for measuring or estimating the energy and carbon footprint of the services running in the edge sites. EC E-C Monitor 118 also monitors the current performance (e.g., latency) of individual services in a service chain (e.g., using tracing - based latency estimation), deployment and traffic path information of the service chain, resource usage (e.g., CPU, memory), etc. The extracted information may be sent to the EC Data Manager 122, e.g., when requested. EC Data Manager 122 may be configured to collect the performance, energy, and carbon information of the microservices from the monitors across edge sites 116. EC data manager 122 may also maintain the service topology (e.g., service dependencies), edge infrastructure topology, cloud-side service chain performance requirements. EC Data Manager 122 may consolidate the measurements/estimations by calculating the performance, energy, and carbon efficiency of possible service paths for a given service chain. The aggregated data may be sent to EC traffic routing manager 114 via the EC exposure 120. EC Traffic Routing Manager 114 may be configured to select an energy and carbon efficiency path fulfilling performance constraints for the request to be handled by the service chain. The calculated traffic path may be then forwarded to the EC microservice instance selector 124 for the application of the path selection. The EC microservice instance selector 124 may convert the selected paths into the configuration to an actuator component (e.g., Ingress Gateway). FIG. 13 shows an example implementation of the network components (e.g., management functions) in a 5G mobile network 100 and edge cloud network 15. The MN E-C monitors 102 and MN data manager 104 can be implemented as part of 3GPP defined Network Data Analytics Function 132 (NWDAF) or MN E-C monitor in an EM 130 and MN data manager 104 in an NWDAF 132. MN E-C monitoring function can be implemented in every independent 5G network user plane and control plane nodes/elements, such as UPF, SMF, AMF and can be part of the Network Manager or Element Manager (EM) 130. MN Data Manager 104 can be part of the NWDAF 132 to collect the MN E-C metrics from 5G network nodes through EM and perform data processing, and estimation. The MN traffic routing manager 106, UPF selector 108, and edge service selector 110 may be implemented into an OAM 134 function. In the edge cloud network 15, the EC E-C monitor 118, EC exposure 120, EC data manager 122, and EC traffic routing manager can be part of one or more edge management systems (e.g., edge management systems 138, 140, which may be the same). Microservice instances selector 124 may be part of an edge application framework 142 such as a service mesh. Example energy and carbon path selection for edge services The data traffic between the end clients (i.e., WDs 22) and the service that contribute to the service’s energy and carbon usage may be widely distributed in the mobile network 100. The WD 22 may communicate with the service from any place within the network coverage area. The service may be deployed in a distributed edge cloud network 15. That is, the energy and carbon usage consumed to transmit the service’s data traffic may be widely distributed to many different geographical locations and is also quite dynamic. In one or more embodiments, service paths that minimize the energy usage and carbon intensity of the service is selected while meeting performance requirements during the service operation. In particular, a traffic path selection policy may be generated that yields the lowest combination of energy usage and carbon intensity for serving the request. An example model of performance, energy usage and carbon intensity at service path level followed by an optimization logic for sustainable request routing may be as follows. Performance metric Latency may be a performance metric. The latency of a given data path i

of a service can be represented as follows: ^^^^^^^_^^^^^^^^^^^ ^^ ^^^^^^^_^^^^^^^^^ ^ ^^^^^^^_^^^^^^^^^ Equation 1 ^^^^^^^_^^^^^^^^^^ represents the summation of the average DL and UL package delay between the UE and the edge sites of a service in the data path dp: ^^^^^^^_^^^^^^^^^^ ^^^^^^^^^_^^^^^^^^ ^ ^^^^^^^_^^^^^^^^^^^^^Equation 2 The values of ^^^ !"#_$%^&^'(^and ^^^ !"#_$%^&^'(^ may depend on the nature of the service, for example, if it is downlink heavy or uplink heavy service. ^^^^^^^_^^^^^^^^^in Equation 1 represents latency of the service introduced inside the edge site. This can be due to communication latency between two dependent microservices distributed across sites (# )^*+!_{^$%^&^,-^-.''^}), queuing latency (# )^*+!_{^$%^&^,-^/0,^}) i.e., when the application cannot immediately attend a request and/or processing latency, i.e., the time it takes for the service to process the request (# )^*+!_{^$%^&^,-^%1.-^}^^and send an acknowledge or response back once the request is attended. ^^^^^^^_^^^^^^^^^ ^ ^^^^^^^_{^^^^^^^^^^2^^^} ^ ^^^^^^^_{^^^^^^^^^34^^}^_^ ^ ^^^^^^^^_{^^^^^^^^^^52^^} Equation 3 Energy usage Metric An example E2E model may be used to estimate the energy consumption and energy efficiency of services based on traffic paths. The example model for a given traffic path may be as follows. The energy usage (in terms of kWh) for a given service data path i can be given as: 67_^$%^&^,^, ^^89_^^^^^^^^^ ^^89_^^^^^^^^^^^^^ Equation 4 where 67_^$%^&^,^,^: 67_^$%^&^'(:and 67_^$%^&^,-^^represent the E2E, mobile network, and edge cloud EC of the data path i for the service respectively. 67_^$%^&^'(^^ can be determined by summing up the EC of all control plane (89_{^^^^^^^^^^^^^^^^;<^^}^^and data plane NFs (89_{^^^^^^^^^^^^^^^^;<^^}^^along the path i introduced for accessing the service and can be given as: 89_^^^^^^^^^ ^^=_;<^^89_{^^^^^^^^^^^^^^^^;<^^} ^^=_;<^^89_{^^^^^^^^^^^^^^^^;<^} Equation 5 89_{^^^^^^^^^^^^^^^^;<^^}and 89_{^^^^^^^^^^^^^^^^;<^^}can be calculated based on the proportion of the EC of the control plane and data plane NF, respectively. This can for example be based on the number of services served by the NF for control plane NF and the ratio of the service in the data path i and total data volume served by the NF for data plane NF. In the edge sites 116, 67_^$%^&^,-^can be calculated based on the energy consumed by all replicates of the service along the data path i, and can be given as: 67_^$%^&^,-^ ^ =_^^=_>=_?^89_{^^^^^^^^^?^>^^^} Equation 6 where 67_{^$%^&^,-^@^AB^} is the EC of the service replicate j in node k of the edge site l along the data path i . Hence the e2e energy consumption can be: 67_^$%^&^,^, ^ ^=_;<^89_{^^^^^^^^^^^^^^^^;<^} ^ ^=_;<^89_{^^^^^^^^^^^^^^^^;<^} ^ =_^^=_>=_?^89_{^^^^^^^^^?^>^^^}^ Equation 3 Carbon intensity Metric The carbon intensity (gram per kWh (g.CO2/KWH)) of a data path i can be calculated based on the carbon intensity of the hops or functional units attributed to the service along a data path. This can correspond to Equation 5 and Equation 6 for the mobile network 100 and edge cloud parts respectively as shown below: 7C_^$%^&^'( ^^=_;<^^9D_{^^^^^^^^^^^^^^^^;<^^} ^^=_;<^^9D_{^^^^^^^^^^^^^^^^;<^}^^ Equation 4 where 9D_{^^^^^^^^^^^^^^^^;<^^}and 9D_{^^^^^^^^^^^^^^^^;<^}represent the carbon intensity of a control and data plane function NF respectively along the path i that is associated with the service. 7C_^$%^&^,- ^ =_^^=_>=_?^9D_{^^^^^^^^^?^>^^^} Equation 9 7C_{^$%^&^,-^@^A^E} represents the carbon intensity of the service replicate j in node k of the edge site l along the data path i . Similar to Equation 7, the e2e carbon intensity can be represented as: 7C_^$%^&^,^, ^^=_;<^^9D_{^^^^^^^^^^^^^^^^;<^^} ^^=_;<^^9D_{^^^^^^^^^^^^^^^^;<^} ^ =_^^=_>=_?^9D_{^^^^^^^^^?^>^^^} Equation 5^ A Coordinated energy and carbon intensity optimization Based on the latency requirement and the current/predicted latency of multiple paths, the traffic routing managers at the mobile network 100 and edge cloud network 15 may select the candidate path(s) that fulfils the latency requirements. There may be more than one path that meets the latency requirement. In this case, the managers may select the paths based on energy usage and carbon intensity. The minimization of energy usage and carbon intensity of data path with a pre-specified latency requirement can be given as: Minimize 67_^$% + 7C_^$% Equation 11 Subject to # )^*+!_^$% < # )^*+!_^FG1H,F The optimization, as shown in Equation 11 may have more than one objective such as minimizing both the energy usage and carbon intensity. One method may include using a scalarization method that transform the problem into a single objective optimization problem. The scalarized function may be represented as a score function and expressed as: Fscore =( ^ x I_^$%)+( ^ x J_^$%) Equation 12 Where Fscore is a weighted sum of the normalized energy usage (I_^$%), and carbon intensity (J_^$%). The normalized values may be between 0 and 1 regardless of the original values. The transformation can be based on the minimum and maximum values. For example, I_^$% can be expressed as:

Equation 13 and the minimum and maximum values can be extracted from by aggregating the minimum and maximum EC and CI of functional units in the path (i.e. NF and service instance). For the service instances in the edge sites 116 for example, the minimum EC and CI of pods (e.g., of a containerized application) can be extracted and/or be idle, and the maximum can be calculated when fully utilized for a given service instance (e.g. when reaching the resource limit). In the mobile network 100, the minimum and maximum values can also be extracted based on minimum and maximum data volume that could be transferred. The ^ and ^ coefficients are weights that represent the importance of energy savings and carbon efficiency respectively, where ^ + ^ =1. The operator or service provider may select these values to handle prioritization between energy usage and carbon intensity in case for energy sources that mixes renewable and fossil-based energy. Search methods can be used to calculate the paths that have the lowest costs, e.g., the lowest combined energy and carbon cost. FIG. 14 shows steps of an example process according to one or more embodiments. At step S300, a service traffic routing path selection operation is initiated. This can be for a request of a batch of requests coming from a given WD 22. Further, step S300 may be performed by any component of system 10 (e.g., such as shown in FIGS. 12 and 13). At step S302, in mobile network 100, MN traffic routing manager 106 requests data to make path selection. Data requested may include network topology (e.g. the NFs and the data paths), performance (e.g., latency), carbon (e.g., g.CO2/KWH), and energy (e.g., KwH) information of the data paths. MN traffic routing manager 106 may contact the MN data manager 104 for the retrieval of such information. At step S304, MN Data Manager 104 requests the various monitors distributed across the mobile network 100 for the collection of low-level data including the performance, energy and carbon information of the various components along the various routing paths. This may include processing information such as delay of the links between the hops/NFs, energy and carbon intensity of the NF, data volume processed by a NF, data volume associated with the requests. It analyzes these information and then aggregates (using for example Equations 2, 5, and 8) to arrive at the path level performance (latency), energy (KwH) and carbon intensity (g.CO2/KWH) information. At step S306, MN data manager 104 sends the consolidated data to the MN traffic routing manager 106 for decision making. At step S308, by analyzing different options, MN traffic routing manager 106 tunes the traffic routing that can fulfil network-side latency requirement and minimize the carbon and energy footprint (e.g. using Equation 11) through UPF selection by interacting with the UPF selector 108. At step S310, UPF selector (e.g. SMF) may update the policy and changes the routing for requests based on the newly selected UPF. At step S312, edge service selector 110 subscribes to UPF selection and network condition (e.g., performance, energy and carbon information using network topology) to the MN Exposure 112 component. At step S314, MN Exposure 112 receives the UPF assignment, and at step S316, edge service selector 110 receives the UPF assignment for the WD 22 from the MN Exposure 112 component. Edge service selector 110 may also receive information about a change in a network condition. At step S318, edge service selector 110 subscribes to the EC exposure 120 to get service status such as deployment status, performance and related information of paths between the UPF to the edge sites, etc. At step S320, edge service selector 110 receives information from the EC exposure 120 to make an edge selection decision. At step S322, based on the received information, edge service selector 110 selects an edge site, e.g., that is hosting the frontend/ingress microservice for the request such that the mobile network- side performance requirement is met and yields low energy and carbon footprint (e.g., lower than a predetermined threshold). FIG. 15 shows other steps of the example process. At step S324, edge service selector 110 sends a DNS response with the external IP address of an Ingress Gateway from the selected edge site 116. At step S326, WD 22 sends the request to the Ingress Gateway (i.e., microservice instance selector 124) accordingly. At step S328, in the edge cloud network 15, EC traffic routing manager 114 subscribes to MN Exposure 112 for events related to traffic routing path selection in mobile network 100. At step S330, EC traffic routing manager 114 receives the edge site selected for the request. At step S332, EC traffic routing manager 114 also receives performance, energy and carbon information of the different paths within the edge cloud from the EC Data Manager. At step S334, EC data manager 122 collects, analyzes and aggregate service and infrastructure level information received from EC E-C monitors 118 distributed across the edge cloud network 15. These may include processing information such as service topology (e.g. service dependencies), edge infrastructure topology (e.g., connections between different edge sites), cloud-side service chain performance requirements, performance, energy and carbon footprints of microservice replicas, etc. EC data manager 122 consolidates the measurements/estimations (e.g., using Equations 3, 6, and 9) to arrive at the performance (e.g. latency), energy (e.g., KwH), and carbon (g.CO2/KWH) footprints of possible service paths for a given service chain. At step S336, EC data manager 122 sends the data to the EC traffic routing manager 114 to make microservice instances selection. At step S338, EC traffic routing manager 114 selects a microservice path, e.g., those instances connected to the ingress services and those that are dependent to each other across sites to form a complete path while fulfilling cloud-side performance requirement, thereby reducing the combined energy and carbon footprints (e.g. using Equation 11). At step S340, EC traffic routing manager 114 sends the new service path selection policy to the microservice instance selector 124 for the configuration of the traffic path. At step S340, microservice instance selector 124 applies the path selection, which may be performed using routing path header injection where the ingress gateway forwards the request to the endpoint of the entry service of the path. In some embodiments, the UPF selector 108 may be (or may be comprised in or comprise) an SMF. MN data manager 104 may be (or may be comprised in or comprise) an NWDAF. The edge service selector 110 may be (or may be comprised in or comprise) a DNS resolver. Further, microservice instance selector 124 may be (or may be comprised in or comprise) an ingress gateway. In some other embodiments, a network path (e.g., E2E network path) is determined based on the selection of mobile network path and edge cloud network path that may optimize the E2E energy usage and E2E carbon intensity. In some embodiments, the selection of the mobile network path is carried out based on the mobile network energy usage and carbon intensity information. Similarly, the edge cloud network path selection is based on edge cloud network energy usage and carbon intensity. E2E consideration may be achieved through the interaction between the mobile network 100 and the edge cloud network 15. In a nonlimiting example, edge site and deployment status information may be used in the mobile network 100 and the mobile network path selection decision (e.g., by the edge cloud network or one or more of its components). In some embodiments, for the selection of both the mobile network and edge cloud network paths, the E2E metrics are considered. In some other embodiments, the selected network path maximizes the E2E energy efficiency metric, the E2E carbon efficiency metric, and meets E2E service performance requirements (or metric). In some embodiments, the selected network path minimizes an E2E energy usage metric (e.g., energy usage) and the E2E carbon intensity metric (e.g., carbon intensity), and meets or exceeds E2E service performance requirements (metrics). In some embodiments, an energy efficiency metric may be based on energy usage. For example, the energy efficiency metric and energy usage may be inversely proportional. Similarly, carbon efficiency metric may be based on the carbon intensity. For example, the carbon efficiency metric and carbon intensity may be inversely proportional. As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, computer program product and/or computer storage media storing an executable computer program. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or “module.” Any process, step, action and/or functionality described herein may be performed by, and/or associated to, a corresponding module, which may be implemented in software and/or firmware and/or hardware. Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices. Some embodiments are described herein with reference to flowchart illustrations and/or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer (to thereby create a special purpose computer), special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. It is to be understood that the functions/acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows. Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Python, Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and/or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination. It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings without departing from the scope of the following claims.

Claims

What is claimed is: 1. A system (10) comprising a wireless device, WD (22), a mobile network (100), and an edge cloud network (15), the WD (22) being configured to communicate with the mobile network (100) and the edge cloud network (15), the mobile network (100) comprising one or more first servers (17), the edge cloud network (15) comprising one or more second servers (17), one or more of the one or more first servers (17) and the one or more second servers (17) being configured to perform steps of a method including: determining an end to end, E2E, service performance metric corresponding to a service provided to the WD (22) by the mobile network (100) and the edge cloud network (15); determining an E2E energy efficiency metric and an E2E carbon efficiency metric corresponding to the service provided to the WD (22) by the mobile network (100) and the edge cloud network (15); determining a network path comprising a mobile network path and an edge cloud network path usable by the mobile network (100) and the edge cloud network (15), respectively, to provide the service, the network path maximizing the E2E energy efficiency metric and the E2E carbon efficiency metric, and meeting or exceeding the E2E service performance metric, the determining of the network path including selecting the network path from a plurality of network paths, the selected network path having the greatest E2E energy efficiency metric and the greatest E2E carbon efficiency metric of each one of the plurality of network paths; and causing the one or more first servers (17) and the one or more second servers (17) to provide the service using the network path.

2. A method in a first network node (16) in a mobile network (100), the first network node (16) being configured to communicate with a second network node (16) in an edge cloud network (15), the method comprising: obtaining (S134), for each one of a plurality of mobile network components, an E2E energy efficiency metric and an E2E carbon efficiency metric corresponding to a service provided to a wireless device, WD (22), at least by the mobile network (100); determining (S136) a mobile network path usable by the mobile network (100) to provide the service, the mobile network path being part of a network path usable by the mobile network (100) and the edge cloud network (15) to provide the service, the mobile network path being determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric; and transmitting (S138) information associated with the mobile network path to the second network node (16).

3. The method of Claim 2, wherein the method further includes: selecting a user plane function, UPF, based on the determined mobile network path.

4. The method of Claim 3, wherein the method further includes: obtaining information corresponding to network routing from the selected UPF to the edge cloud network (15).

5. The method of any one of Claims 3 and 4, wherein the method further includes: updating a policy and changing the network routing for service requests based on the selected UPF.

6. The method of any one of Claims 3-5, wherein the method further includes: selecting an edge site based on the selected UPF and service information, the edge site hosting the service, the selected edge site being included in the information associated with the mobile network path.

7. The method of any one of Claims 2-6, wherein the mobile network path is further based on an E2E service performance metric corresponding to the service provided to the WD (22) by the mobile network (100) and the edge cloud network (15).

8. The method of Claim 7, wherein the E2E service performance metric is based on a first delay and a second delay, the first delay being between the WD (22) and the edge cloud network (15), the first delay being associated with the service, the second delay being between the service and another service of a different edge site.

9. The method of any one of Claims 2-8, wherein one or both of: the E2E energy efficiency metric is based on energy usage for a data path including the mobile network (100) and the edge cloud network (15); and the E2E carbon efficiency metric is based a first carbon intensity of the data path, the first carbon intensity of the data path being based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path.

10. The method of any one of Claims 2-8, wherein the first network node (16) comprises a network data analytics function, NWDAF.

11. A first network node (16) in a mobile network (100), the first network node (16) being configured to communicate with a second network node (16) in an edge cloud network (15) and configured to perform any one of steps corresponding to Claims 2-10.

12. A method in a second network node (16) in an edge cloud network (15), the second network node (16) being configured to communicate with a first network node (16) in a mobile network (100) and a wireless device, WD (22), the method comprising: receiving (S140), from the first network node (16), information associated with a mobile network path, the mobile network path being usable at least by the mobile network (100) to provide a service to the WD (22); obtaining (S142), for each one of a plurality of edge cloud network components, an end to end, E2E, energy efficiency metric and an E2E carbon efficiency metric corresponding to the service provided to the WD (22) at least by the edge cloud network (15); determining (S144) an edge cloud network path usable by the edge cloud network (15) to provide the service, the edge cloud network path being determined based on the E2E energy efficiency metric and the E2E carbon efficiency metric; determining (S146) a network path usable by the mobile network (100) and the edge cloud network (15) to provide the service, the network path comprising the mobile network path and the edge cloud network path, the network path being determined based on the information associated with the mobile network path, the edge cloud network path, the E2E energy efficiency metric, and the E2E carbon efficiency metric; and causing (S148) one or more edge cloud network components of the plurality of edge cloud network components to provide the service using the network path.

13. The method of Claim 12, wherein the method further includes: receiving, from the WD (22), a service request corresponding to the service, the service request being based on a domain name system, DNS, response provided by the first network node (16), the DNS response including an external address of an ingress gateway associated with an edge site of the edge cloud network (15).

14. The method of Claim 13, wherein the method further includes: selecting the edge cloud network path based on service instances connected to the ingress gateway and other service instances depending on at least one other service instance across edge sites, the selected cloud edge network path being usable to determine the network path.

15. The method of any one of Claims 12-14, wherein the method further includes: determining a network path selection policy for the configuration of the network path based at least on the E2E energy efficiency metric and the E2E carbon efficiency metric.

16. The method of any one of Claims 12-15, wherein determining the edge cloud network path is further based on an E2E service performance metric corresponding to the service provided to the WD (22) by the mobile network (100) and the edge cloud network (15).

17. The method of Claim 16, wherein the E2E service performance metric is based on a first delay and a second delay, the first delay being between the WD (22) and the edge cloud network (15), the first delay being associated with the service, the second delay being between the service and another service of a different edge site.

18. The method of any one of Claims 12-17, wherein one or both of: the E2E energy efficiency metric is based on energy usage for a data path including the mobile network (100) and the edge cloud network (15); and the E2E carbon efficiency metric includes a first carbon intensity of the data path, the first carbon intensity of the data path being based on a second carbon intensity of one or both of hops and functional units attributed to the service along the data path.

19. The method of any one of Claims 12-18, wherein the method further includes: applying the network path using routing path header injection.

20. The method of any one of Claims 12-19, wherein the method further includes: subscribing to the first network node (16) to receive the information associated with the mobile network path, the information including events related to selection of the mobile network path.

21. The method of any one of Claims 12-20, wherein the information associated with the mobile network path includes edge site information.

22. The method of any one of Claims 12-20, wherein one or both of: the service is a microservice; and the one or more components include one or more servers (17).

23. A second network node (16) in an edge cloud network (15), the second network node (16) being configured to communicate with a first network node (16) in a mobile network (100) and a wireless device, WD (22), the second network node being configured to perform one or more steps corresponding to any one of Claims 12-22.