Method for efficient power-aware offloading of data processing

Abstract

In an aspect, the present disclosure relates to a method of a device (110, 113, 211, 230) of offloading processing of data of a User Equipment (110, UE) to a computing device. The method comprises acquiring (S101a-d, S102a-d) an energy supply metric of a plurality of computing devices (140-143) being capable of offloading the UE (110) for processing of data, the energy supply metrics indicating energy source types from which each computing device (140-143) is supplied with energy, determining (S103) whether or not one or more of the energy supply metrics comply with a set energy supply criterion, and if so selecting (S104), for offloading processing of data of the UE (110), at least one of the computing devices (140) having an energy supply metric complying with the set energy supply criterion.

Description

METHOD FOR EFFICIENT POWER-AWARE OFFLOADING OF DATA PROCESSINGTECHNICAL FIELD

[0001] The present disclosure relates to a method of a device of offloading processing of data of a User Equipment (UE) to a computing device, and a device performing the method.BACKGROUND

[0002] In state-of-the-art wireless communication systems, various sites or radio equipment are commonly supplied with energy from different sources such as wind, solar, battery, fuel cell, electric grid, etc. Further, the electric grid may in its turn be supplied with energy from different types of source such as hydroelectric, nuclear, coal, oil, etc.

[0003] In these wireless communication systems, the supply of energy from one or more sources to access nodes are controlled by central communication system radio equipment, such as e.g. a radio base station (RBS), and the selection of energy sources for the access nodes is undertaken based on RBS power consumption and usage.

[0004] In communication systems, computational offloading mechanisms may be provided to delegate processing of data from one device to another with more suitable data processing capabilities. A common aim is to transfer the task of processing data from a device with limited resources to a device with great resources in terms of computational power, such as an edge server or cloud server. These resources include battery, storage, processing capacity and network capabilities and performance objectives include e.g. reduced computation times, minimizing network resource usage, maximizing battery life, decreasing device heating, etc.

[0005] However, offloading of processing of data from one device to another in the prior art does not take into account type of energy source utilized for supplying the device to which the data processing is offloaded.SUMMARY

[0006] An objective is to solve, or at least mitigate, this problem in the art and to provide an improved method of offloading processing of data of a UE to a computing device.

[0007] This objective is attained in a first aspect by a method of a device of offloading processing of data of a UE to a computing device. The method comprises acquiring an energy supply metric of a plurality of computing devices being capable of offloading the UE for processing of data, the energy supply metrics indicating energy source types from which each computing device is supplied with energy, determining whether or not one or more of the energy supply metrics comply with a set energy supply criterion, and if so selecting, for offloading processing of data of the UE, at least one of the computing devices having an energy supply metric complying with the set energy supply criterion.

[0008] This objective is attained in a second aspect by a device configured to offload processing of data of a UE to a computing device. The device comprises a processing unit and a memory, said memory containing instructions executable by said processing unit, whereby the device is operative to acquiring an energy supply metric of a plurality of computing devices being capable of offloading the UE for processing of data, the energy supply metrics indicating energy source types from which each computing device is supplied with energy, determining whether or not one or more of the energy supply metrics comply with a set energy supply criterion, and if so to selecting, for offloading processing of data of the UE, at least one of the computing devices having an energy supply metric complying with the set energy supply criterion.

[0009] In prior art solutions, the UE cannot make energy aware data processing offloading decisions based on the energy sources that are available to the computing devices to which UE data processing is to be offloaded.Advantageously, with embodiments disclosed herein, offloading decisions truly becomes energy aware.

[0010] By evaluating acquired energy supply metrics indicating energy source types from which each computing device is supplied with energy, the UE canoffload the data processing to a desired computing device and e.g. advantageously select the most sustainable combination of energy sources.[oon] In an embodiment, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device of the computing device being supplied with renewable energy to a highest extent.

[0012] In an embodiment, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device of the computing device being supplied with renewable energy to a highest extent from a specific energy source.

[0013] In an embodiment, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device of the computing device being supplied with renewable energy from a rechargeable battery having a highest charge of all the rechargeable batteries supplying the computing devices.

[0014] In an embodiment, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device of the computing device being supplied with energy at a currently lowest cost.

[0015] In an embodiment, the energy source types comprising one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

[0016] In an embodiment, the device performing the method is a radio base station or the UE itself or steps of the method are distributed among the two.

[0017] In a third aspect, a computer program is provided comprising computer-executable instructions for causing a device of the second aspect to perform steps recited in the method of the first aspect when the computerexecutable instructions are executed on a processing unit included in the device.

[0018] In a fourth aspect, a computer program product is provided comprising a computer readable medium, the computer readable medium having the computer program according to the third aspect embodied thereon.

[0019] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / an / the element, apparatus, component, means, step, etc." are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Aspects and embodiments are now described, by way of example, with reference to the accompanying drawings, in which:

[0021] Figure 1 illustrates a communication network in which embodiments maybe implemented;

[0022] Figure 2 illustrates an edge device being supplied with energy from multiple sources;

[0023] Figure 3 shows a signalling diagram illustrating a method according to an embodiment;

[0024] Figure 4 shows a fifth generation core network in which embodiments maybe implemented;

[0025] Figure 5 shows a radio base station in which embodiments may be implemented;

[0026] Figure 6 shows a radio site implementing embodiments;

[0027] Figure 7 shows a signalling diagram illustrating a method according to an embodiment;

[0028] Figure 8 illustrates a device according to an embodiment; and

[0029] Figure 9 illustrates a network in which embodiments may be implemented.DETAILED DESCRIPTION

[0030] Figure 1 illustrates a simplified version of a communication system 100 where a first set of devices no, 111, 112 in the form of User Equipment (UE), e.g. smart phones, tablets, desktops gaming consoles, connected vehicles, etc., are served by a first radio base station 113 (RBS), while second set of UEs 120, 121, 122 are served by a second RBS 123.

[0031] Each RBS 113, 123 is connected to a core network 130, such has e.g., a 3rdGeneration Partnership Project (3GPP) 5thgeneration core (5GC) network, and the 5GC network 130 may in its turn connected to a plurality of edge devices 140- 143 embodied in the form or for instance computer devices, routers, data centres, virtual machines, etc.

[0032] The edge devices 140-143 are typically in their turn connected via theInternet to one or more cloud servers 150. While the edges devices 140-143 in Figure 1 are arranged upstream of the core network 130, one or more of the edge devices 140-143 may alternatively be arranged downstream of the core network 130, and connected directly to (or embedded with) any one of the RBSs 113, 123.

[0033] With the edge devices 140-143, computing capability is brought closer to the edge of the 5GC network 130 and thus closer to the end-users being the UEs 110-112, 120-122. This facilitates shorter response time, higher data security and lower power consumption. A great advantage in using edge devices is that processing-heavy tasks normally performed at the UEs 110-112, 120-122, e.g. different types of data encoding and computation, maybe offloaded from the UEs 110-112, 120-122, to the edge devices 140-143.

[0034] As previously mentioned, an issue to be resolved in the art is how to, when offloading processing of data from one device to another, take into account type of energy source utilized for supplying the device to which the data processing is offloaded.

[0035] In embodiments to be disclosed hereinbelow, the device that a UE offloads data processing to is exemplified in the form of an edge device. However, offloading may in practice occur to any appropriate device capable of performingcomputational tasks on behalf of the UE such as for instance a device included in the 5GC network 130 or the cloud server 150.

[0036] Figure 2 illustrates an edge device 140 being supplied with energy from four different energy sources S1-S4, where Si denotes wind, S2 is solar, S3 is electric grid and S4 is a backup battery. As is understood, the different energy sources S1-S4 may be utilized to supply the edge device 140 also in a scenario where the edge device 140 is arranged to be directly connected to or embedded with any one of the RBSs 113, 123.

[0037] Assuming for instance that a first UE no makes a request via first RBS 113 to offload data processing to either one of first edge device 140, second edge device 141, third edge device 142 or fourth edge device 143 with the preference that the offloading is performed to the edge device out of the four edge devices 140-143 which is being supplied with renewable energy to a highest extent. In the example below, all four devices 140-143 are assumed to be supplied with energy from the four different energy sources S1-S4.

[0038] Figure 3 shows a signalling diagram further illustrating the exemplifying embodiment.

[0039] In first steps Sioia-d, first UE 110 acquires information regarding the energy sources S1-S4 of each edge device 140-143 in the form of an energy supply metric. For instance, this information maybe required by the UE no directly from each edge device 140-143 (as shown) or by making a request to the RBS 113 which in its turn acquires the information from each edge device 140-143.

[0040] The edge devices 140-143 responds in steps i02a-d by providing the energy supply metric indicating from which different energy source the respective edge device is supplied.

[0041] As illustrated with the energy supply metrics provided in steps Si02a-d, the first edge device 140 is supplied with Si: 30% wind, S2: 30% solar, S3: 20% electric grid and S4: 20% battery. As is understood, the wind and solar energy may be produced locally at the edge devices.

[0042] The second edge device 141 is supplied with Si: 0% wind, S2: 30% solar, S3: 60% electric grid and S4: 10% battery. Thus, it maybe that the second edge device 141 is either not supplied at all with wind energy or that there is no wind energy available currently due to windless conditions.

[0043] The third edge device 142 is supplied with Si: 20% wind, S2: 0% solar, S3: 70% electric grid and S4: 10% battery. Thus, it maybe that the third edge device 142 is either not supplied at all with solar energy or that there is no solar energy available currently due to e.g. cloudy weather.

[0044] Finally, the third edge device 142 is supplied with Si: 20% wind, S2: 0% solar, S3: 80% electric grid and S4: 0% battery. Thus, it maybe that the third edge device 142 is either not supplied at all with solar energy or that there is no solar energy available currently. As regards battery power S4, it may be that the third edge device 142 lacks back-up battery or that there is no power available in the battery at the moment.

[0045] In step S103, based on the energy supply metrics acquired through steps Si02a-d, the UE no determines which one of the edge devices 140-143 should be selected for offloading UE data processing, given that the currently set energy supply criterion stipulating that the edge device being supplied with renewable energy to the highest extent should be complied with.

[0046] In this example, the energy supplied via the electric grid is not considered to originate from a renewable source, wherein the first edge device 140 is supplied with 30% wind and 30% solar, i.e. in total 60% renewable energy. This number is far higher than the second device 141 being supplied with a total of 30% renewable energy, while the third edge device 142 and the fourth edge device 143 only is supplied with 20% renewable energy each.

[0047] As a result, the UE no will offload the data processing to the first edge device 140 in this exemplifying embodiment and advantageously select the most sustainable combination of energy sources resulting in the first edge device 140 being supplied with 60% renewable energy.

[0048] In another example, it is assumed that the wind and solar sources Si, S2 are used to charge a local battery unless the generated power is not instantly consumed by the respective edge device.

[0049] In such example, the energy supply criterion to be complied with in step S103 is that the edge device having the highest charged battery should be used. Assuming for instance that the battery of the first edge device 140 has a charge of 20%, while the battery of the second edge device 141 and that of the third edge device 142 both has a charge of 10%, and the battery of the fourth edge device 143 has a charge of 80%.

[0050] Advantageously, the UE no will in step S103 conclude that the battery of the fourth edge device 143 has the highest charge and will thus offload processing of data to the fourth edge device 143, thereby making sure to use the almost fully charged battery of the fourth edge device 143 in order to make good use of stored energy (rather than e.g. using the electric grid). Further advantageous is that the battery having the highest surplus energy is utilized in this case.

[0051] In yet an example, again using the energy supply metrics illustrated in Figure 3; assuming that the energy cost at the given time of day if the energy is consumed from the electric grid. In such a scenario, the UE no would in step S103 conclude that the fourth edge device 143 is supplied to a highest degree from the electric grid out of the four edge devices 140-143. Thus, the energy cost is the lowest if the fourth edge device 143 is offloaded to in step S104.

[0052] In a further example, assuming that solar should be favoured before any other energy source type. If so, it can be seen in Figure 3 that both the first edge device 140 and the second edge device 141 is supplied with 30% solar energy, while neither of the third edge device 142 and the fourth edge device 143 is supplied with solar energy.

[0053] Thus, both the first edge device 140 and the second edge device 141 complies with the energy supply criterion in S103 that the edge device which is being supplied with solar energy to a greatest extent should be offloaded to in S104.

[0054] It may thus be envisaged that one of the first edge device 140 and the second edge device 141 is selected by the UE no for offloading in S104.Alternatively, it may be envisaged that some of the processing tasks to be offloaded is offloaded to the first edge device 140 while some other of the tasks are offloaded to the second edge device 141.

[0055] It may further be envisaged that admission control is enforced, where for instance an edge device which is not supplied from a renewable source to a sufficient degree simply cannot be selected for offloading.

[0056] While in this exemplifying embodiment the first UE no performs the steps of acquiring the energy supply metrics in Sioia-d and Si02a-d, determining in S103 whether or not one or more of the energy supply metrics comply with a set energy supply criterion, and finally selecting in S104 to which edge device 140-143 to offload the processing of data, it is envisaged that all these steps of Figure 3 may be performed for instance by the RBS 113 or some other appropriate equipment in the wireless communication network 100 on behalf of the first UE no. Thus, the RBS 112 may be configured with an offloading manager for determining whether or not there is capacity at one or more of the edge nodes 140-143 in addition to determining from the energy supply metrics to which edge node(s) to offload UE data processing.

[0057] It may further be envisaged that one or more steps are performed by the first UE no while one or more of the steps are performed by the RBS 113 in a distributed manner. In an example, the first UE 110 may make an offloading request to the RBS 113 which acquires the energy supply metrics of the edge device 140-143 and then determines to which edge device 140-143 the offloading is to be performed before finally effecting the offloading of the data processing from the first UE 110 to the selected one(s) of the edge devices 140-143.

[0058] In prior art solutions, the UE 110 or RBS 113 cannot make energy aware data processing offloading decisions based on the energy sources S1-S4 that are available. Advantageously, with embodiments disclosed herein, offloading decisions truly becomes energy aware.

[0059] Any devices exchanging data representing the energy supply metrics maybe equipped with a set of standardized application programming interfaces (APIs) to retrieve such data in a machine-readable format such as JSON (“JavaScript Object Notation”).

[0060] In the following, an embodiment will be described as being implemented in connection to a 5GC network. The radio base station in 5G is commonly referred to as a gNodeB (gNB). Figure 4 in the following will illustrate a 5GC while Figure 5 will illustrate a gNB.

[0061] Figure 4 thus illustrates a core network of a 5G communication system - commonly referred to as New Radio (NR) - being connected to a Radio Access Network (RAN) 212 comprising a plurality of gNBs (not shown) serving a UE 211 via Uu interface. The RAN 212 is connected to a data network (DN) 213 such as the Internet. The 5GC comprises a number of entities referred to as Network Functions (NFs) which will be described in the following.

[0062] Control plane signal paths are illustrated with dotted lines while user plane signal paths are illustrated with continuous lines.

[0063] A User Plane Function (UPF) 210a is a service function that processes user plane packets; processing may include altering the packet’s payload and / or header, interconnection to data network(s), packet routing and forwarding, etc. A number of UPFs 210a, 210b maybe utilized being interconnected via N9 interface. As can be seen, the RAN 212 is connected to the UPF 210a via N3 interface and further to the data network 213 via N6 interface.

[0064] Further, the 5GC comprises a Network Exposure Function (NEF) 214 for exposing capabilities and events, an NF (Network Function) Repository Function (NRF) 215 for providing discovery and registration functionality for NFs, a Policy Control Function (PCF) 216, Unified Data Management (UDM) 217 for storing subscriber data and profiles, and an Application Function (AF) 218 for supporting application influence on traffic routing.

[0065] Moreover, the 5GC comprises an Authentication Server Function (AUSF) 219 storing data for authentication of the UE 211, an Access and Mobility Function (AMF) 220 for providing UE-based authentication, authorization,mobility management, etc., a Session Management Function (SMF) 221 configured to perform session management, e.g. session establishment, modify and release, etc., and a Network Slice Selection Functions (NSSF) 222 which allows an improved isolation and separation between slices.

[0066] As shown, all core network NFs except the UPFs 210a, 210b are connected to a core network service bus.

[0067] Figure 5 illustrates a gNB 230 communicating with a neighbouring gNB 240 over an Xn interface. The gNBs 230, 240 form part of a RAN referred to as New Generation (NG) RAN.

[0068] The gNB 230 comprises a central unit (CU) being split into a CU-CP 231 (“control plane”) and a CU-UP 232 (“user plane”) being interconnected over an El interface. Again, control plane signal paths are illustrated with dotted lines while user plane signal paths are illustrated with continuous lines.

[0069] The CU-CP 232 connects to an AMF 220 of the 5GC network over interface N2 carrying control plane signalling via Nil, the SMF 221 and N4 to the UPF 210a, while the CU-UP 231 connects to a data network 213, such as the Internet, over N6 via N3 interface and a UPF 210a for transporting user data.

[0070] Further, the CU-CP 232 connects to a distributed unit 233a (DU) via interface Fi-C and further to one or more UEs 2iia-c via evolved Common Public Radio Interface (eCPRI) and radio units 234a, 234b (RUs) communicating over wireless interface Uu, while the CU-UP 231 connects to a DU 233b via interface Fi- U and further on to the UEs 2iia-c via interface eCPRI, the RUs 234c, 234b and the wireless interface Uu.

[0071] Figure 6 illustrates a physical radio site 250 being supplied with four different energy / power sources S1-S4 as previously illustrated with reference to Figure 2, where Si denotes wind, S2 is solar, S3 is electric grid and S4 represents a backup battery.

[0072] In Figure 6, data signal paths are illustrated with dotted lines while power supply paths are illustrated with continuous lines.

[0073] Each source S1-S3 is generally connected to a power supply unit 260, 261, 262 (PSU) which converts the alternating high voltage current (AC) into direct current (DC), and may also regulate the DC output voltage to comply with voltage supply tolerances.

[0074] The output of each PSU 260-262 is then connected to a power distribution unit 263 (PDU) for distributing the supplied power to the equipment accommodated on the radio site 250. The backup battery source S4 maybe directly connected directly to the PDU 263.

[0075] Further shown is a so-called site controller 264 (SC) orchestrating the sources S1-S4 for optimal control. The SC 264 is generally used to monitor, collect and store data related to power usage, voltage levels, current, temperature, etc.

[0076] In the embodiment illustrated in Figure 6, the SC 264 the may be equipped with an entity (embodied by means of software and / or hardware) referred to as an energy mix collector (EMC) configured to acquire the energy source metrics previously discussed in detail with reference to Figure 3 and to determine how to offload UE 211 given a currently set energy criterion.

[0077] The gNB 230 previously described in detail with reference to Figure 5 communicates with the UE 211 over the wireless interface Uu. It should be understood that the gNB 230 in practice typically may communicate with hundreds of UEs. However, for brevity, only a single UE 211 is illustrated in Figure 6.

[0078] As previously described, the gNB 230 is connected via the N2 and N3 interface to a 5GC network 265 (only selected NFs are shown in Figure 6) and further to an edge device 266 (ED) via the UPF 210 and interface N6, which interface N6 further connects the UE 211 to a data network 213 such as the Internet.

[0079] In this embodiment, the edge device 266 is connected to the NEF 214 of the 5GC network 265 via an interface referred to as Ned, and an NF referred to as a Power Service Function 267 (PSF) connect to the AMF 220 via an interface Npsf is introduced in the 5GC network 265. The 5GC network 265 is furthsr connected to the SC 264.

[0080] Figure 7 shows a signalling diagram further illustrating the embodiment of Figure 6 where entities of the physical radio site 250 communicates with each other for acquiring energy supply metric in order to determine if and how the UE 211 is to be offloaded.

[0081] The UE 211 may be arranged with functionality in the form of a UE power agent (UP A) for assessing energy supply metric and an edge enabler client (EEC) fr performing the offloading.

[0082] Similar to the embodiment described with reference to Figure 3, the UE 211 or the RBS (i.e. the gNB 230 in Figure 6) may gather energy supply metrics and determine any offloading to be undertaken from the metrics. However, communication in Figure 7 is undertaken over other entities as compared to that of Figure 3.

[0083] In first steps S20ia-d, first UE no acquires information regarding the energy sources S1-S4 of edge device 266 in the form of an energy supply metric.

[0084] Thus, the UE 211 corresponds over Uu with the gNB 230 (not shown in Figure 7) to request one or more energy supply metrics in 201a. The request is passed over N3 and the UPF 210 and further via N6 to the edge device 266.

[0085] The edge device 266 will in its turn communicate the request to the NEF 214 in 8201b, the NEF 214 will send the request to the PSF 267 in S201C, which finally will send the request to the site controller 264 in S20id. As previously mentioned, the site controller 264 has access to the energy supply metrics of the site 250.

[0086] For instance, similar to what previously as described with reference to Figure 3, the site controller 264 may respond in 8202a by providing the energy supply metric indicating from which different energy sources the edge device 266 is supplied, i.e. Si: 30% wind, S2: 30% solar, S3: 20% electric grid and S4: 20% battery.

[0087] This metric is then returned to the PSF 267 in 8202b, which further sends the metric to the NEF 214 in S202C, which in its turn forwards the metric tothe edge device 266 in S202C, wherein the edge device 266 finally delivers the energy supply metric to the UE 211 (via the gNB 230) in S202d.

[0088] As is understood, similar to Figure 3, energy supply metrics would hence be acquired for a number of different edge devices (only one edge device 266 is being illustrated in Figure 6) and in S203, based on the energy supply metrics of the different edge devices, the UE 211 determines which one of said different edge devices should be selected for offloading UE data processing in S204, given a currently set energy supply criterion.

[0089] Figure 8 illustrates a device no (such as e.g. a UE) configured to offload processing of data to a computing device according to an embodiment, e.g. a selected one of the edge devices 140-143 of Figure 1. As previously mentioned, other devices may be suitable for determining if the UE no is to be offloaded and selecting a computing device to which to offload the UE 110, such as an RBS.

[0090] The steps of the method performed by the UE 110 are in practice performed by a processing unit 811 embodied in the form of one or more microprocessors arranged to execute a computer program 812 downloaded to a storage medium 813 associated with the microprocessor, such as a Random Access Memory (RAM), a Flash memory or a hard disk drive. The processing unit 811 is arranged to cause the UE 110 to carry out the method according to embodiments when the appropriate computer program 812 comprising computer-executable instructions is downloaded to the storage medium 813 and executed by the processing unit 811. The storage medium 813 may also be a computer program product comprising the computer program 812. Alternatively, the computer program 812 maybe transferred to the storage medium 813 by means of a suitable computer program product, such as a Digital Versatile Disc (DVD) or a memory stick. As a further alternative, the computer program 812 maybe downloaded to the storage medium 813 over a network. The processing unit 811 may alternatively be embodied in the form of a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc. The UE no further comprises a communication interface 814 (wired or wireless) over which it is configured to transmit and receive data.

[0091] The device determining whether to offload the UE 211 based on acquired energy supply metrics, e.g. the UE 211 itself or the gNB 230 according to embodiments, may be provided as a standalone device or as a part of at least one further device. Alternatively, functionality of the UE and / or gNB may be distributed between at least two devices, or nodes. These at least two nodes, or devices, may either be part of the same network part (such as the core network) or maybe spread between at least two such network parts. In general terms, instructions that are required to be performed in real time maybe performed in a device, or node, operatively closer to a radio cell than instructions that are not required to be performed in real time.

[0092] Thus, a first portion of the instructions performed by the UE and / or gNB may be executed in a first device, and a second portion of the of the instructions performed by the NEF may be executed in a second device; the herein disclosed embodiments are not limited to any particular number of devices on which the instructions performed by the UE and / or gNB may be executed.

[0093] Hence, the methods according to the herein disclosed embodiments are suitable to be performed by a device residing in a cloud computational environment. Therefore, although a single processing circuitry 810 is illustrated in Figure 8, the processing circuitry 810 maybe distributed among a plurality of devices, or nodes.

[0094] Figure 9 illustrates a network in the form of an Open RAN 101 (O-RAN), in which embodiments maybe implemented. For example, the method maybe implemented in an O-eN 300.

[0095] With reference to the O-RAN 100, the role of a Non-Real Time RAN intelligent controller (RIC) 200 is among other things, such as providing a service management and orchestration framework, to serve one or more radio base stations 300 (i.e. RAN sites) referred to as O-eNB via 01 interface and to provide high-level control signals to Near-Real Time RICs 400 via Al interface; such signals include but not limited to policy-based guidance, machine-learning (ML) model management, and enrichment of data. The role of Near-Real Time RICs 400 is to perform low-level control signals to O-RAN compatible network elementsincluding the one or more O-eNBs 300, O-CU-CP 500, O-CU-UP 600 and O-DU 700 via E2 interface. Further included is an O-RU 800 connected to the O-DU 700 via a control, user and synchronization (CUS) plane as well as via a management (M) plane, and an O-Cloud 900, i.e. a cloud platform.

[0096] The aspects of the present disclosure have mainly been described above with reference to a few embodiments and examples thereof. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the invention, as defined by the appended patent claims.

[0097] Thus, while various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Claims

CLAIMS1. Method of a device (no, 113, 211, 230), of offloading processing of data of a User Equipment (no), UE, to a computing device, comprising: acquiring (Sioia-d, Si02a-d) an energy supply metric of a plurality of computing devices (140-143) being capable of offloading the UE (110) for processing of data, the energy supply metrics indicating energy source types from which each computing device (140-143) is supplied with energy; determining (S103) whether or not one or more of the energy supply metrics comply with a set energy supply criterion; and if so selecting (S104), for offloading processing of data of the UE (110), at least one of the computing devices (140) having an energy supply metric complying with the set energy supply criterion.

2. The method of claim 1, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy to a highest extent.

3. The method of claims 1 or 2, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy to a highest extent from a specific energy source.

4. The method of any one of the preceding claims, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy from a rechargeable battery having a highest charge of all the rechargeable batteries supplying the computing devices (140-143).

5. The method of any one of the preceding claims, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with energy at a currently lowest cost.

6. The method of any one of the preceding claims, the energy source types comprising one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

7. The method of any one of the preceding claims, the device performing the method being a radio base station (no, 230) or the UE (no, 211) itself or steps of the method being distributed among the two.

8. A computer program (812) comprising computer-executable instructions for causing a device (110, 113, 211, 230) to perform steps recited in any one of claims 1- 7 when the computer-executable instructions are executed on a processing unit (811) included in the device (110, 113, 211, 230).

9. A computer program product comprising a computer readable medium (813), the computer readable medium having the computer program (812) according to claim 8 embodied thereon.

10. A device (110, 113, 211, 230) configured to offload processing of data of a User Equipment (no), UE, to a computing device, said device comprising a processing unit (811) and a memory (813), said memory containing instructions (812) executable by said processing unit (811), whereby the device is operative to: acquiring (Sioia-d, Si02a-d) an energy supply metric of a plurality of computing devices (140-143) being capable of offloading the UE (110) for processing of data, the energy supply metrics indicating energy source types from which each computing device (140-143) is supplied with energy; determining (S103) whether or not one or more of the energy supply metrics comply with a set energy supply criterion; and if so selecting (S104), for offloading processing of data of the UE (no), at least one of the computing devices (140) having an energy supply metric complying with the set energy supply criterion.

11. The device (no, 113, 211, 230) of claim 10, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy to a highest extent.

12. The device (no, 113, 211, 230) of claims 10 or 11, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy to a highest extent from a specific energy source.

13. The device (no, 113, 211, 230) of any one of claims 10-12, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with renewable energy from a rechargeable battery having a highest charge of all the rechargeable batteries supplying the computing devices (140-143).

14. The device (110, 113, 211, 230) of any one of claims 10-13, the energy supply metric complying with the set energy supply criterion being the energy supply metric indicating a computing device (140) of the computing device (140-143) being supplied with energy at a currently lowest cost.

15. The device (no, 113, 211, 230) of any one of claims 10-14, the energy source types comprising one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

16. The device (no, 113, 211, 230) of any one of claims 10-15, the device being configured to offload the processing of data being a radio base station (110, 230), or the UE (110, 211) itself.

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