Energy-efficient offloading of data processing

Abstract

In an aspect, a method of a network node (113) serving a UE (110) of offloading processing of data of the UE (110) to a computing device (140-143) is provided. The method comprises receiving (S101) a request to offload processing of data of the UE (110), acquiring (S102) information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed, identifying (S103) one or more computing devices (140, 141) to which the offloading can be performed based on the acquired information, selecting (S104), from the identified one or more computing devices (140, 141), a computing device (140) to which to offload the requested data processing, and a network node configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with, and offloading (S105) the processing of data to the selected computing device (140).

Description

ENERGY-EFFICIENT OFFLOADING OF DATA PROCESSINGTECHNICAL FIELD

[0001] The present disclosure relates to a method of a network node serving a User Equipment (UE) of offloading processing of data of the UE to a computing device, and a network node performing the method. Further disclosed are a computer program and a computer program product.BACKGROUND

[0002] Governments and industries have set ambitious targets to reduce their greenhouse gas (GHG) emissions and deal with global warming. The telecommunication sector has set stringent requirements for both energy efficiency and consumption in their networks.To support the growing use of fifth generation (5G) connectivity and its more stringent requirements in terms of energy consumption, while reducing energy consumption through an intelligent use of the network, changes are needed at all levels to achieve maximum effect. Mobile Network Operators (MNOs) must provide new approaches to network planning, deployment, management, and optimization that have energy efficiency as their core, and are implemented end-to-end. Studies have shown that a 5G network, despite its enhanced energy efficiency in bits per Joule due to its larger bandwidth and better spatial multiplexing capabilities, could typically consume over 140% more energy than a fourth generation (4G) network, with a similar coverage area. This unwanted energy consumption arises from sG’s greater density of radio base stations (RBSs), antennas, cloud infrastructure, and user equipment (UE), among others.

[0003] Apart from that, sixth generation (6G) networks will support trillions of embedded devices, including devices operating without batteries, ambient or zero energy internet-of-Things (loT) devices, using energy harvesting. Deploying such "zero energy devices" will remove existing use case limitations associated with battery replacement or charging requirements. Several research challenges have been already identified that must be addressed before zero-energy or extremely low power devices can become a reality. This includes energy harvesting and storage and a system design handling a very large number of devices.

[0004] One of the services that is envisaged as part of future 5G / 6G platforms is computational offloading. Specifically, MNOs will likely want to offer a dynamic, lightweight, and highly granular computational offloading service to mobile devices. Here, the core idea is to expand application functionality from the connected UE, for example, mobile phones, drones, extended reality (XR) glasses, or loT devices (including zero energy devices), to a compute environment that is part of the network, e.g., collocated with network infrastructure and functions, which poses challenges in terms of energy consumption.

[0005] US 10,440,096 B2 discloses methods provided for offloading computationally intensive tasks from one computer device to another computer device taking into account, inter alia, energy consumption and latency budgets for both computation and communication.SUMMARY

[0006] One objective is to solve, or at least mitigate, the problems in the art and thus to provide an improved method of a radio base station serving a User Equipment (UE) of offloading processing of data of the UE to a computing device.

[0007] This objective is attained in a first aspect by a method of a network node serving a UE of offloading processing of data of the UE to a computing device. The method comprises receiving a request to offload processing of data of the UE, acquiring information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed, identifying one or more computing devices to which the offloading can be performed based on the acquired information, selecting, from the identified one or more computing devices, a computing device to which to offload the requested data processing, and a network node configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with, and offloading the processing of data to the selected computing device.

[0008] This objective is attained in a second aspect by a network node serving a UE, the network node being configured to offload processing of data of the UE to a computing device. The network node comprises a processing unit and a memory, said memory containing instructions executable by said processing unit, whereby the network node is operative to receive a request to offload processing of data of the UE,acquire information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed, identify one or more computing devices to which the offloading can be performed based on the acquired information, select, from the identified one or more computing devices, a computing device to which to offload the requested data processing, and a network node configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with, and to offload the processing of data to the selected computing device.

[0009] Advantageously, with embodiments disclosed herein, based on information acquire information indicating estimated computing resources required for performing the processing of data to be offloaded and a time at which the processing of data is to be performed, which e.g. may be acquired from the UE, the network node will be able to estimate network utilisation for the requested offloading when selecting one or more computing device to which to offload the data processing, and further to determine which network node configuration to utilize.

[0010] In an embodiment, operational parameters of the UE are acquired and taken into account upon selecting a computing device to which to offload the requested data processing and a network node configuration to be utilized.

[0011] In an embodiment, the energy efficiency criterion stipulates that temporarily stored power should be prioritized before power instantly generated by a power source.

[0012] In an embodiment, the energy efficiency criterion stipulates that the data processing should be scheduled at low-traffic time periods for the network node.

[0013] In an embodiment, the network node configuration includes number of radio units at the network node being activated and / or transmission power utilized by the radio units.

[0014] In an embodiment, the computing devices are collocated with the network node on a same radio site.

[0015] In an embodiment, the energy efficiency criterion stipulates that non-fossil power sources should be prioritized before fossil power sources.

[0016] In an embodiment, the energy efficiency criterion stipulates that one or more specific types of non-fossil power sources should be prioritized.

[0017] In an embodiment, the power source types comprise one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

[0018] In an embodiment, power source information is acquired indicating which types of power sources are available, which information is being taken into account upon selecting a computing device to which to offload the requested data processing and a network node configuration to be utilized.

[0019] In an embodiment, operational parameters of the computing devices are acquired and taken into account upon selecting a computing device to which to offload the requested data processing and a network node configuration to be utilized.

[0020] In a third aspect, a computer program is provided comprising computerexecutable instructions for causing a network node to perform steps recited in the method of the first aspect when the computer-executable instructions are executed on a processing unit included in the network node.

[0021] 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.

[0022] 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

[0023] Aspects and embodiments are now described, by way of example, with reference to the accompanying drawings, in which:

[0024] Figure 1 illustrates a communication network in which embodiments may be implemented;

[0025] Figure 2 shows a signalling diagram illustrating a method according to an embodiment;Figure 3 shows a fifth-generation core network in which embodiments may be implemented;

[0026] Figure 4 shows a radio base station in which embodiments may be implemented;

[0027] Figure 5 shows a radio site implementing embodiments;

[0028] Figure 6 shows a signalling diagram illustrating a method according to an embodiment;

[0029] Figure 7 illustrates a radio base station device according to an embodiment; and

[0030] Figure 8 illustrates a network in which embodiments may be implemented.DETAILED DESCRIPTION

[0031] The aspects of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the invention are shown.

[0032] These aspects may, however, be embodied in many different forms and should not be construed as limiting; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and to fully convey the scope of all aspects of invention to those skilled in the art. Like numbers refer to like elements throughout the description.

[0033] Figure 1 illustrates a simplified version of a communication system 100 where a first set of devices 110, 111, 112 in the form of User Equipment (UE), e.g. smart phones, tablets, desktops, gaming consoles, connected vehicles, Internet-of- Things (loT) devices, etc., are served by a network node which in this example is embodied in the form of a first radio base station 113 (RBS), while second set of UEs 120, 121, 122 are served by a network node in the form of a second RBS 123.

[0034] The network nodes 113, 123 may be composed of multiple physically separate components (e.g., a NodeB component and a radio network controller (RNC) component, or a base transceiver station (BTS) component and a base station controller (BSC) component, etc.), which may each have their own respective components. In certain scenarios in which the network nodes 113, 123 comprisemultiple separate components (e.g., BTS and BSC components), one or more of the separate components maybe shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network nodes 113, 123 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components maybe duplicated (e.g., separate memory for different RATs) and some components may be reused (e.g., a same antenna may be shared by different RATs). The network nodes 113, 123 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network nodes 113, 123, for example Global System for Mobile Communications (GSM), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), New Radio (NR), WiFi, Zigbee, Z-wave, Long Range Wide Area Network (LoRaWAN), Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network nodes 113, 123. The network nodes 113, 123 will in the following be exemplified in the form of RBSs.

[0035] Each RBS 113, 123 is connected to a core network 130, such has e.g., a 3rd Generation 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.

[0036] The edge devices 140-143 are typically in their turn connected via the Internet 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. In such scenario, the edge devices 140-143 are commonly referred to as being collocated with the RBSs 113, 123.

[0037] 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 no- 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-heavytasks normally performed at the UEs 110-112, 120-122, e.g. different types of data encoding and computation, may be offloaded from the UEs 110-112, 120-122, to the edge devices 140-143. As previously discussed, attaining energy efficiency is a challenge when offloading processing of data from a UE 110 to an edge device 140 in the communication system 100 illustrated in Figure 1.

[0038] Figure 2 shows a signalling diagram illustrating an embodiment where this issue is resolved. In this exemplifying embodiment, it is assumed with reference to Figure 1 that UE 110 wishes to offload processing of data to one or more of the edge devices 140-143, in the following referred to as computing devices, via RBS 113.

[0039] Hence, in a first step S101, the UE 110 sends a request to offload processing of data to the RBS 113.

[0040] In S102, the RBS 113 acquires information indicating estimated computing resources required for performing the offloaded processing of data and time at which the processing of data is estimated to be performed.

[0041] In this exemplifying embodiment, it is assumed that the UE 110 estimated resources and time, in this example [data compression ratio, file size, reoccurrence frequency]. As is understood, it may be envisaged that the UE 110 indicates already with the request in S101 that the UE 110 wishes to compress a great data set at a reoccurring instance of time. Thus, based on this information provided by the UE 110 to the RBS 113, the RBS 113 will advantageously be able to estimate network utilisation for the requested offloading, and further to determine which RBS configuration to utilize, as will be discussed in the following.

[0042] However, as is understood, it may that the RBS 113 turns to the computing devices 140-143 for a given data processing service to be offloaded in order to acquire estimated computing resources for performing the service. It may also be that the service is to be performed at one time only, which may or may not be critical as indicated by the UE 110. It may for instance be that the UE 110 allows the RBS 113 to determine when the data processing is to be performed, in which case the RBS 113 may select an optimal processing time from an energy efficiency perspective, for instance during a time of day when price of electricity, or the load on the network, is low, thereby avoiding processing at radio peak hours. It is envisaged that the RBS 113may turn to one or more of the computing devices 140-143 for determining the time at which the processing is to be performed.

[0043] This same communication channel would also supply estimated performance requirements to the base station, so that the offloaded task could be deployed to a low energy requirement compute resource when execution time is not crucial.

[0044] Thereafter, in S103, the RBS 113 identifies one or more computing devices to which offloading can be performed based on the acquired information. In this example, it is assumed that all four computing devices 140-143 are capable of compressing a data set of the indicated size at the indicated data compression ratio, but that only the first computing device 140 and the second computing device 141 are capable of performing the data compression at a reoccurring frequency of, say, every 12 hours. In another example, it is envisaged that the recurrence frequency is not specified by the UE 110, in which case, the RBS 113 advantageously may select to perform the data processing specified with the offloading request at a point in time where network traffic is low and as a result select a computing device having capacity to perform the data processing at said point in time. Advantageously, a more effective usage of network resources is attained.

[0045] Thus, the RBS 113 identifies the first and second computing devices 140, 141 in S103 as being capable of compressing the indicated data set every 12 hours.

[0046] In S104, the RBS 113 selects a computing device to which to offload the requested data processing such that a set energy efficiency criterion is complied with. In this example, the energy efficiency criterion stipulates that non-fossil power sources should be prioritized if available, and that solar and wind should be prioritized before hydro. Assuming for instance that the first computing device 140 is powered by a hydroelectric source while the second computing device 141 is powered by a solar source and that the indicated time of processing with a periodicity of 12 hours occurs at night when the sun does not shine. In such scenario, due to the unavailability of solar power at night, the first computing device 140 will be selected rather than the second computing device 141. As is understood, there may be scenarios where fossil power sources are prioritized, for example if non-fossil power sources currently are unavailable or if the non-fossil power sources currently do not produce power.

[0047] As is understood, should the indicated time of processing with periodicity of 12 hours occur at daytime, the second computing device 141 would typically have been selected given that the energy efficiency criterion stipulates that solar and wind should be prioritized before hydro.

[0048] Further in S104, the RBS 113 selects an RBS configuration to be utilized. Again, assuming that the indicated time of processing with periodicity of 12 hours occurs at night when there typically are fewer UEs connected to the RBS 113, the RBS 113 may reconfigure its radio units to reduce transmission power, if the energy efficiency criterion stipulates that the RBS configuration should be selected with the objective to reduce radio power consumption. Finally in S105, the data processing is offloaded to the selected computing device 140.

[0049] Advantageously, with this embodiment, energy efficiency is taken into account at all times upon offloading UE data processing to one or more computing devices, both in terms of computing device power consumption and RBS power consumption.

[0050] The set energy efficiency criterion may advantageously relate to sustainable power source selection or prioritization.

[0051] Further advantageous is that this embodiment enables estimated computing resource information acquired from the UE to be used to dynamically adapt RBS configuration and consequent energy usage as application requirements change. As previously mentioned, based on the information provided by the UE 110 to the RBS 113, the RBS 113 will advantageously be able to estimate network utilisation for the requested offloading, in addition to determining which RBS configuration to utilize.

[0052] Conventionally, a UE passively receives information as to resource availability and / or cost from an RBS and may decide whether offloading to a computing device via the RBS is beneficial, or whether the task should be recalled or transferred to another RBS. Thus, in the art, the UE it is not capable of influencing the configuration of the RBS.

[0053] 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 toas a gNodeB (gNB). Figure 3 in the following will illustrate a 5GC while Figure 5 will illustrate a gNB.

[0054] Figure 3 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 110 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. As previously mentioned, while the computing devices 140-143 illustrated in Figure 1 may be collocated with gNBs in the RAN 212, they may alternatively be located upstream of the RAN 212 in (or close to) the data network 213.

[0055] Control plane signal paths are illustrated with dotted lines while user plane signal paths are illustrated with continuous lines.

[0056] 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 may be 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.

[0057] 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.

[0058] Moreover, the 5GC comprises an Authentication Server Function (AUSF) 219 storing data for authentication of the UE 110, 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.

[0059] As shown, all core network NFs except the UPFs 210a, 210b are connected to a core network service bus.

[0060] Figure 4 illustrates a gNB 113 capable of communicating with a neighbouring gNB 123 over an Xn interface. The gNBs 113, 123 form part of a RAN referred to as New Generation (NG) RAN.

[0061] The gNB 113 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.

[0062] 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. Thus, as was discussed previously with reference to the signalling diagram of Figure 2, the gNB 113 may receive a request for offloading of data processing from UE 110 in S101 along with estimated processing resources in S102 over interface Uu, whereupon the gNB 113 may identify computing devices (not shown in Figure 4) via CU-UP 231, interface N3 and UPF 210a in S103, select appropriate computing devices in S104 along with RBS configuration to be utilized, for instance by adjusting transmission power of one or more of the RUs 234a-234d and offload the data processing in S105 to a selected computing device.

[0063] Further, the CU-CP 232 connects to a distributed unit 233a (DU) via interface Fi-C and further to one or more UEs 110-112 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 110-112 via interface eCPRI, the RUs 234c, 234d and the wireless interface Uu.

[0064] Figure 5 illustrates a physical radio site 250 being supplied with four different energy / power sources S1-S4, where Si denotes wind, S2 is solar, S3 is electric grid and S4 represents a backup battery.

[0065] In Figure 5, data signal paths are illustrated with dotted lines while power supply paths are illustrated with continuous lines.

[0066] 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.

[0067] 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 may be directly connected directly to the PDU 263.

[0068] 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.

[0069] In the embodiment illustrated in Figure 5, 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 power source information.

[0070] The gNB 113 previously described in detail with reference to Figure 4 communicates with the UE 110 over the wireless interface Uu (via selected RUs, not shown in Figure 5, but previously illustrated in Figure 4 as RUs 2343-d). It should be understood that the gNB 113 in practice typically may communicate with hundreds of UEs over interface Uu in steps S101 and S102. However, for brevity, only a single UE 110 is illustrated in Figure 5.

[0071] As previously described, the gNB 113 is connected via the N2 and N3 interface to a 5GC network 265 (only selected NFs are shown in Figure 5) and further to a collocated computing device 140 (CD) via the UPF 210 and interface N6, which interface N6 further connects the UE 110 to a data network 213 such as the Internet. As is understood, the gNB 113 typically communicates with numerous computing devices, even if a single computing device 140 is shown in Figure 5, with which the gNB 113 communicates in S103, S104 and S105 over interface N3 via the UPF 210 and further via interface N6.

[0072] In this embodiment, the computing device 140 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 Npsfis introduced in the 5GC network 265. The 5GC network 265 is further connected to the SC 264.

[0073] Figure 6 shows a signalling diagram further illustrating the embodiment of Figure 5 where the gNB 113 communicates with various entities of the physical radio site 250 determine if and how the data processing of the UE 211 is to be offloaded such that a set energy efficiency criterion is complied with.Similar to Figure 2, in a first step S101, the UE 110 sends over the Uu interface a request to offload processing of data to the RBS 113. For instance, it may be that the UE 110 wishes to have a data set encoded from a first to a second format, which requires a certain processing capacity.

[0074] In S102, the RBS 113 acquires information indicating estimated computing resources required for performing the offloaded processing of data and time at which the processing of data is estimated to be performed. As previously mentioned, the RBS 113 may advantageously select to perform the data processing specified with the offloading request at a point in time where network traffic is low, in case no specific time is stated.

[0075] While the estimated computing resources required for performing the offloaded processing of data is provided to the RBS 113 in S102, other parameters maybe provided in a further step SiO2a (or with step S102), such as e.g. reference signal received power (RSRP), QoS (“Quality of Service”), Class Identifier (QCI), throughput and latency of data transmitted, etc. As is understood, one or more parameters may continuously be monitored and taken into account by the RBS 113 in S103 and S104.

[0076] In this embodiment, the gNB 113 will further turn to the SC 264 in SiO2b for determining which power source (or mix of power sources) to be utilized upon the data processing being offloaded to a computing device. As previously mentioned, the SC 264 orchestrates the power 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.

[0077] Further, the gNB 113 turns in S1O2C to the PSF 267 which via the NEF 214 can gather operational parameters from the computing device 140, such as e.g. processor type being utilized, storage capacity, power consumption, etc., in order tobe able to determine in S103 to which computing device the requested data processing is to be offloaded.

[0078] In S104, the gNB 113 selects a computing device to which to offload the requested data processing, and a gNB configuration to be utilized, such that a set energy efficiency criterion is complied with.

[0079] In this example, it is assumed that the first computing device 140 is selected for the offloading out of a number of computing devices, for instance since the first computing device 140 is the only device having available computing resources to be instantly used (the UE 110 may have requested immediate processing).

[0080] Now, the energy efficiency criterion may in this example stipulate that any stored power preferably should be used, as compared to e.g. power drawn from the grid. Advantageously, the wind and solar sources Si, S2 may be used to charge a local battery (not shown) unless the generated power is not instantly consumed by other entities on the site 250. In such an example, the generated wind and / or solar power need not be instantly consumed.

[0081] The gNB 113 will thus in S104 conclude from the information previously received from the SC 256 that the first computing device should perform the requested processing of data and that the first computing device 140 should be powered from the charged local battery in order to make good use of stored energy (rather than e.g. using instantly produced solar or wind power).

[0082] It may be envisaged that temporarily stored power is used if other available power sources are not sustainably generated. If the power of the source is generated by e.g. solar or wind, then that may be used in preference to battery power in order to save the battery for another occasion.

[0083] Further, given that the UE 110 may have reported e.g. a high QCI and / or RSRP, the gNB 113 may conclude that either a lesser number of RUs are required in communicating with the UE 110, or that less RU transmission power is required, and the gNB configuration is adjusted accordingly, which provides for even further energy efficiency. For instance, as indicated in S104, the gNB 113 may send a control command to one (or more) of its RUs 264a to lower the transmission power. Finally in S105, the data processing is offloaded to the selected computing device 140.

[0084] Figure 7 illustrates an RBS 113 configured to offload processing of data from a UE to a computing device according to an embodiment. The steps of the method performed by the RBS 113, i.e. the receiving of a request to offload processing of data of a UE in S101, the acquiring of information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed in S102, the identifying of one or more computing devices to which the offloading can be performed based on the acquired information in S103, and the selecting a computing device to which to offload the requested data processing, and a radio base station configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with, 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 RBS 113 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 may be 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 may be 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 RBS 113 further comprises a communication interface 814 (wired or wireless) over which it is configured to transmit and receive data.

[0085] The RBS 113 determining whether to offload the UE according to embodiments may be provided as a standalone device or as a part of at least one further device. Alternatively, functionality of the RBS 113 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 may be spread between at least two such network parts. In general terms, instructions that are required to beperformed in real time may be performed in a device, or node, operatively closer to a radio cell than instructions that are not required to be performed in real time.

[0086] Thus, a first portion of the instructions performed by the RS 113 may be executed in a first device, and a second portion of the of the instructions 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 RBS 113 may be executed.

[0087] 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 may be distributed among a plurality of devices, or nodes.

[0088] Figure 8 illustrates a network in the form of an Open RAN 101 (O-RAN), in which embodiments may be implemented. For example, the method may be implemented in an O-eNB 300.

[0089] 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 elements including the one or more O- eNBs 300, O-CU-CP 500, O-CU-UP 600 and 0-DU 700 via E2 interface. Further included is an 0-RU 800 connected to the 0-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. Similar to the embodiment described with reference to Figure 4, the eNB 300 may communicate with UEs (not shown) via the 0-DU 700 and the 0-RU 800 in steps S101 and S102 and identify, select and offload to computing devices in S103-S105 via the O-CU-UP 600.

[0090] 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 disclosedabove are equally possible within the scope of the invention, as defined by the appended patent claims.

[0091] 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 network node (113) serving a User Equipment (110), UE, of offloading processing of data of the UE (110) to a computing device (140-143), comprising: receiving (S101) a request to offload processing of data of the UE (110); acquiring (S102) information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed; identifying (S103) one or more computing devices (140, 141) to which the offloading can be performed based on the acquired information; selecting (S104), from the identified one or more computing devices (140, 141), a computing device (140) to which to offload the requested data processing, and a network node configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with; and offloading (S105) the processing of data to the selected computing device (140).

2. The method of claim 1, further comprising: acquiring (SiO2a) operational parameters of the UE (110) being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

3. The method of any one of the preceding claims, the energy efficiency criterion stipulating that temporarily stored power should be prioritized before power instantly generated by a power source.

4. The method of any one of the preceding claims, the energy efficiency criterion stipulating that the data processing should be scheduled taking into account time periods for network node traffic.

5. The method of any one of the preceding claims, the network node configuration including number of radio units (2643-d), RUs, at the network node (113) beingactivated and / or transmission power utilized by the radio units (2643-d).

6. The method of any one of the preceding claims, the computing devices (140- 143) being collocated with the network node (113) on a same radio site (250).

7. The method of any one of the preceding claims, the energy efficiency criterion stipulating that non-fossil power sources should be prioritized before fossil power sources.

8. The method of claim 7, the energy efficiency criterion stipulating that one or more specific types of non-fossil power sources should be prioritized.

9. The method of claim 8, the power source types comprising one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

10. The method of any one of the preceding claims, further comprising: acquiring (SiO2b) power source information indicating which types of power sources are available, which information is being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

11. The method of any one of the preceding claims, further comprising: acquiring (SiO2c) operational parameters of the computing devices (140-143) being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

12. A computer program (812) comprising computer-executable instructions for causing the network node (113) to perform steps recited in any one of claims 1-11 when the computer-executable instructions are executed on a processing unit (811) included in the network node (113).13- A computer program product comprising a computer readable medium (813), the computer readable medium having the computer program (812) according to claim 12 embodied thereon.

14. Network node (113) serving a User Equipment (110), UE, the network node (113) being configured to offload processing of data of the UE (110) to a computing device (140-143), the network node (113) comprising a processing unit (811) and a memory (813), said memory containing instructions (812) executable by said processing unit (811), whereby the network node (113) is operative to: receive (S101) a request to offload processing of data of the UE (110); acquire (S102) information indicating estimated computing resources required for performing the processing of data and a time at which the processing of data is to be performed; identify (S103) one or more computing devices (140, 141) to which the offloading can be performed based on the acquired information; select (S104), from the identified one or more computing devices (140, 141), a computing device (140) to which to offload the requested data processing, and a network node configuration to be utilized, the selection being performed such that a set energy efficiency criterion is complied with; and to offload (S105) the processing of data to the selected computing device (140).

15. The network node (113) of claim 14, further being operative to: acquire (SiO2a) operational parameters of the UE (110) being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

16. The network node (113) of claims 14 or 15, the energy efficiency criterion stipulating that temporarily stored power should be prioritized before power instantly generated by a power source.

17. The network node (113) of any one of claims 14-16, the energy efficiency criterion stipulating that the data processing should be scheduled at low-traffic timeperiods for the network node (113).

18. The network node (113) of any one of claims 14-17, the network node configuration including number of radio units (264a-d), RUs, at the network node (113) being activated and / or transmission power utilized by the radio units (264a-d).

19. The network node (113) of any one of claims 14-18, the computing devices (140- 143) being configured to be collocated with the network node (113) on a same radio site (250).

20. The network node (113) of any one of claims 14-19, the energy efficiency criterion stipulating that non-fossil power sources should be prioritized before fossil power sources.

21. The method of claim 7, the energy efficiency criterion stipulating that one or more specific types of non-fossil power sources should be prioritized.

22. The network node (113) of claim 21, the power source types comprising one or more of solar, wind, hydroelectric, electric grid, batteries, fuel cells.

23. The network node (113) of any one of claims 14-22, further being operative to: acquire (SiO2b) power source information indicating which types of power sources are available, which information is being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

24. The network node (113) of any one of claims 14-23, further being operative to: acquiring (SiO2c) operational parameters of the computing devices (140-143) being taken into account upon selecting (S104) a computing device (140) to which to offload the requested data processing and a network node configuration to be utilized.

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