Communication method and apparatus

Abstract

The present application relates to the field of communications, and discloses a communication method and apparatus, capable of improving the model inference energy efficiency. The communication method comprises: a first node sends, to a second node, first information for querying processing capability and / or energy supply information of at least one third node; the first node receives, from the second node, second information indicating the processing capability and / or energy supply information of the at least one third node; and the first node determines, on the basis of the second information, at least one target third node for executing a task.

Description

Communication method and device

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on December 15, 2023, with application number 202311739904.1 and application name “Communication Method and Device,” the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communications, and in particular to communication methods and devices. Background Art

[0003] In the field of artificial intelligence (AI) / machine learning (ML), the number of model parameters is rapidly expanding. This trend brings more accurate results and better performance, but also increases energy consumption. AI / ML energy consumption is affected by multiple factors. Overall, model energy consumption is primarily distributed between training and inference execution. Of these two parts, inference execution accounts for 80% to 90% of the energy consumption, meaning that the model's energy consumption is primarily concentrated in inference execution.

[0004] The 3rd Generation Partnership Project (3GPP) Release 18 AIMLMGMT project studied model lifecycle management. Discussions are currently underway within the standards body for Release 19, with preliminary agreement that Release 19 will further research the sustainability of AI / ML, focusing on energy consumption and efficiency.

[0005] Therefore, how to reduce the energy consumption of inference execution in the AI / ML field and improve the energy efficiency of model inference is an urgent problem that needs to be solved. Summary of the Invention

[0006] The present application provides a communication method and device for improving the energy efficiency of model reasoning.

[0007] To achieve the above objectives, this application adopts the following technical solutions:

[0008] In a first aspect, a communication method is provided, which is applied to a first node. The method may be performed by the first node, a component or device (e.g., a processor, chip, or chip system) applied to the first node, or a logic module or software capable of implementing all or part of the functions of the first node. The communication method includes: sending first information to a second node to query the processing capacity and / or energy supply information of at least one third node; receiving second information from the second node indicating the processing capacity and / or energy supply information of at least one third node; and determining at least one target third node for executing a task based on the second information.

[0009] In the first aspect, the first node first queries the second node about the processing capacity and / or energy supply information of the third node, and then determines the target third node for performing the task based on the processing capacity and / or energy supply information of the third node, so that the selected target third node can have lower energy consumption (and / or lower carbon emissions) when performing the task, thereby improving the energy efficiency during the task execution process.

[0010] In combination with the first aspect, in a possible implementation, the method may further include: sending third information to the second node, wherein the third information is used to indicate a third node that needs to obtain the execution result of the task and at least one target third node.

[0011] In this implementation, the first node notifies the second node through the third information to indicate the third node and the target third node from which the execution result of the task needs to be obtained, thereby enabling the execution of the task.

[0012] In combination with the first aspect, in one possible implementation, the second information includes identification information of at least one third node and corresponding energy supply information; the method also includes: determining the time for each target third node to perform the task according to the energy supply information in the second information.

[0013] In this implementation, the first node can determine the time for each target third node to perform the task based on the energy supply information, thereby ensuring the execution of the task.

[0014] In combination with the first aspect, in a possible implementation, the first information is further used to indicate range information of a third node that needs to be queried.

[0015] In this implementation, the first node also indicates the range information of at least one third node through the first information. After receiving the first information, the second node can feedback the processing capability and / or power supply information of the third node within the range information indicated by the first information to the first node. The range information indicates the geographical range of the third node that needs to be queried. By limiting the query to the third nodes within a certain range, the subsequent transmission overhead can be reduced.

[0016] In combination with the first aspect, in a possible implementation, the method further includes: sending sixth information to the second node, where the sixth information indicates a historical processing result of the calling task.

[0017] In this implementation, the first node indicates the historical processing results of the calling task, and uses the historical processing results to replace the actual task execution process, which can reduce the computing power required to execute the task and thereby improve the energy efficiency during the task execution process.

[0018] In combination with the first aspect, in one possible implementation, the task includes at least one of the following: model training, model testing, model simulation, model loading, or model reasoning.

[0019] In combination with the first aspect, the processing capability includes at least one of the following: hardware processing capability, storage capability, or hardware energy efficiency information; the energy supply information includes at least one of the following: the type of energy supplied, the energy available time, or the carbon emissions corresponding to each unit of energy.

[0020] In a second aspect, a communication method is provided, which is applied to a second node. The method may be performed by the second node, a component or device (e.g., a processor, chip, or chip system) applied to the second node, or a logic module or software that implements all or part of the functions of the second node. The communication method includes: receiving first information, the first information being used to query the processing capability and / or energy supply information of at least one third node; determining second information based on the first information, the second information indicating the processing capability and / or energy supply information of the at least one third node; and sending the second information.

[0021] In the second aspect, the second node first receives first information for querying the processing capability and / or energy supply information of at least one third node, and determines second information indicating the processing capability and / or energy supply information of at least one third node based on the first information, and then sends the second information to the first node, so that the first node can determine the target third node for performing the task based on the processing capability and / or energy supply information of the third node, so that the selected target third node can have lower energy consumption (and / or lower carbon emissions) for performing the task, thereby improving energy efficiency during the task execution process.

[0022] In combination with the second aspect, in a possible implementation, the method also includes: receiving third information, the third information is used to indicate the third node that needs to obtain the execution result of the task and the target third node for executing the task; sending fourth information to the target third node that executes the task, wherein the fourth information indicates the third node that needs to obtain the execution result of the task.

[0023] In this implementation, the second node determines the third node and the target third node that need to obtain the execution result of the task based on the third information, and then notifies the target third node that executes the task based on the fourth information which is the third node that needs to obtain the execution result of the task, so that the execution of the task can be realized.

[0024] In combination with the second aspect, in a possible implementation, the method further includes: receiving sixth information, wherein the sixth information indicates a call history processing result; and sending the sixth information to a target third node.

[0025] In this implementation, sixth information indicating the historical processing results of the called task is received and sent to the target third node, so that the target third node can use the historical processing results to replace the actual task execution process, thereby reducing the computing power required to execute the task and improving the energy efficiency during the task execution process.

[0026] In combination with the second aspect, in a possible implementation, the first information is further used to indicate range information of the third node that needs to be queried.

[0027] In this implementation, after receiving the first information, the second node can feedback the processing capability and / or energy supply information of the third node within the range information indicated by the first information to the first node. The range information indicates the geographical range of the third node that needs to be queried. By limiting the query to the third nodes within a certain range, the subsequent transmission overhead can be reduced.

[0028] In conjunction with the second aspect, in one possible implementation, the method further includes:

[0029] Acquire processing capability and / or energy supply information of at least one third node.

[0030] In this implementation, the second node obtains the processing capacity and / or energy supply information of the third node, which can be used by the first node to determine the target third node for executing the task based on the strategy of reducing energy consumption / reducing carbon emissions, thereby improving the energy efficiency of task processing.

[0031] In a third aspect, a communication method is provided for use with a third node executing a task (i.e., a target third node). The method may be performed by the target third node, a component or device (e.g., a processor, chip, or chip system) applied to the target third node, or a logic module or software capable of implementing all or part of the functions of the target third node. The communication method includes: receiving fourth information, wherein the fourth information indicates a third node for which an execution result of a task needs to be obtained; receiving task parameters required for executing the task; executing the task according to the task parameters to obtain an execution result of the task; and sending the execution result to the third node for which the execution result of the task needs to be obtained.

[0032] In the third aspect, the target third node executes the task based on the task parameters and sends the execution result to the third node that needs to obtain the execution result of the task, thereby meeting the task requirements of the third node that needs to obtain the execution result of the task.

[0033] In combination with the third aspect, in a possible implementation, the third node that executes the task stores historical task parameters and corresponding historical processing results; the task is executed according to the task parameters to obtain the execution result of the task, including: determining the target historical processing result as the execution result of the task, wherein the historical task parameters corresponding to the target historical processing result match the task parameters.

[0034] In this implementation, the target third node uses historical processing results instead of the actual task execution process, which can reduce the computing power required to execute the task and thus improve the energy efficiency during the task execution process.

[0035] Optionally, in this implementation, the target third node may determine the target historical processing result as the execution result of the task after receiving the sixth information indicating the call of the historical processing result.

[0036] In a fourth aspect, the present application provides a communication device, which may be a first node or a chip or system on chip in the first node. The communication device may implement the functions performed by the first node in the above-mentioned first aspect or a possible design of the first aspect, and the functions may be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-mentioned functions. For example, the communication device includes: a transceiver module for sending first information to a second node, the first information being used to query the processing capability and / or energy supply information of at least one third node; the transceiver module is also used to receive second information, the second information indicating the processing capability and / or energy supply information of at least one third node; and a processing module for determining at least one target third node for performing a task based on the second information.

[0037] In combination with the fourth aspect, in a possible implementation, the device also includes: a transceiver module, used to send third information to the second node, wherein the third information is used to indicate a third node that needs to obtain the execution result of the task and at least one target third node.

[0038] In combination with the fourth aspect, in one possible implementation, the second information includes identification information of at least one third node and corresponding energy supply information; the processing module is also used to: determine the time for each target third node to perform the task based on the energy supply information in the second information.

[0039] In combination with the fourth aspect, in a possible implementation, the first information is further used to indicate range information of the third node that needs to be queried.

[0040] In combination with the fourth aspect, in a possible implementation, the transceiver module is further used to: send sixth information to the second node, where the sixth information indicates a historical processing result of the calling task.

[0041] In conjunction with the fourth aspect, in one possible implementation, the task includes at least one of the following: model training, model testing, model simulation, model loading, or model reasoning.

[0042] In combination with the fourth aspect, the processing capability includes at least one of the following: hardware processing capability, storage capability, or hardware energy efficiency information; the energy supply information includes at least one of the following: the type of energy supplied, the energy available time, or the carbon emissions corresponding to each unit of energy.

[0043] In a fifth aspect, the present application provides a communication device, which may be a second node or a chip or system on chip in the second node. The communication device may implement the functions performed by the second node in the above-mentioned second aspect or the possible design of the second aspect, and the functions may be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-mentioned functions. For example, the communication device includes: a transceiver module for receiving first information, the first information being used to query the processing capability and / or energy supply information of at least one third node; a processing module for determining second information based on the first information, the second information indicating the processing capability and / or energy supply information of at least one third node; and a transceiver module for sending the second information.

[0044] In conjunction with the fifth aspect, in one possible implementation, the transceiver module is further configured to receive third information, where the third information is used to indicate a third node that needs to obtain an execution result of the task and a target third node for executing the task;

[0045] The transceiver module is further configured to send fourth information to a target third node for executing the task, wherein the fourth information indicates the third node that needs to obtain the execution result of the task.

[0046] In conjunction with the fifth aspect, in one possible implementation, the transceiver module is further configured to:

[0047] receiving sixth information, wherein the sixth information indicates a call history processing result;

[0048] The sixth information is sent to the target third node.

[0049] In combination with the fifth aspect, in a possible implementation, the first information is also used to indicate range information of the third node that needs to be queried.

[0050] In conjunction with the fifth aspect, in one possible implementation, the processing module is further configured to:

[0051] The processing capability and / or energy supply information of at least one third node is obtained through the transceiver module.

[0052] In a sixth aspect, the present application provides a communication device, which may be a target third node or a chip or system on chip in the target third node. The communication device may implement the function performed by the target third node in the third aspect or a possible design of the third aspect, and the function may be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, the communication device includes: a transceiver module for receiving fourth information, wherein the fourth information indicates the third node for which the execution result of the task needs to be obtained; the transceiver module is also used to receive the task parameters required for executing the task; a processing module is used to execute the task according to the task parameters and obtain the execution result of the task; the transceiver module is also used to send the execution result to the third node for which the execution result of the task needs to be obtained.

[0053] In combination with the sixth aspect, in one possible implementation, the third node that executes the task stores historical task parameters and corresponding historical processing results; the processing module is specifically used to determine the target historical processing result as the execution result of the task, wherein the historical task parameters corresponding to the target historical processing result match the task parameters.

[0054] In a seventh aspect, the present application provides a communication device, comprising a processor and a transceiver, wherein the processor and the transceiver are configured to support the communication device in executing the method of the first aspect. Furthermore, the communication device may further comprise a memory storing computer instructions, and the processor may execute the computer instructions to execute the method of the first aspect, the second aspect, or the third aspect.

[0055] In an eighth aspect, the present application provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed, the method of the first aspect, the second aspect or the third aspect is executed.

[0056] In a ninth aspect, the present application provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the method of the first, second or third aspect described above.

[0057] In a tenth aspect, the present application provides a chip comprising a processor and a transceiver, wherein the processor and the transceiver are used to support a communication device to execute the method of the first aspect, the second aspect or the third aspect.

[0058] In an eleventh aspect, the present application provides a communication system, comprising a first node and a second node, wherein the first node is configured to execute the method of the first aspect, and the second node is configured to execute the method of the second aspect.

[0059] Optionally, the communication system may further include a third node, and the third node is used to execute the method of the third aspect.

[0060] Among them, the beneficial effects described in the fourth to eleventh aspects of this application can refer to the beneficial effect analysis of the first, second or third aspects, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] FIG1 is a schematic diagram of an AI / ML workflow provided in an embodiment of the present application;

[0062] FIG2 is a schematic diagram of the architecture of a communication system provided in an embodiment of the present application;

[0063] FIG3 is a schematic diagram of the architecture of another communication system provided in an embodiment of the present application;

[0064] FIG4 is a schematic diagram of the architecture of another communication system provided in an embodiment of the present application;

[0065] FIG5 is a schematic diagram of the architecture of another communication system provided in an embodiment of the present application;

[0066] FIG6 is a schematic diagram of the architecture of another communication system provided in an embodiment of the present application;

[0067] FIG7 is a schematic diagram of the architecture of another communication system provided in an embodiment of the present application;

[0068] FIG8 is a flow chart of a communication method provided in an embodiment of the present application;

[0069] FIG9 is a flow chart of another communication method provided in an embodiment of the present application;

[0070] FIG10 is a flow chart of another communication method provided in an embodiment of the present application;

[0071] FIG11 is a flow chart of another communication method provided in an embodiment of the present application;

[0072] FIG12 is a flow chart of another communication method provided in an embodiment of the present application;

[0073] FIG13 is a flow chart of another communication method provided in an embodiment of the present application;

[0074] FIG14 is a flow chart of another communication method provided in an embodiment of the present application;

[0075] FIG15 is a schematic structural diagram of a communication device provided in an embodiment of the present application;

[0076] FIG16 is a schematic structural diagram of another communication device provided in an embodiment of the present application;

[0077] FIG17 is a schematic structural diagram of another communication device provided in an embodiment of the present application;

[0078] FIG18 is a schematic structural diagram of another communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0079] Before introducing the embodiments of the present application, some terms involved in the embodiments of the present application are explained as shown in Table 1.

[0080] Table 1

[0081] The existing AI / ML workflow is shown in Figure 1 and primarily consists of a training phase (model training and testing), a simulation phase (model simulation), a deployment phase (model loading), and an inference phase (model inference). During the deployment phase, the model generated during the training phase is loaded into the target inference function for execution during the inference phase. Current AI / ML workflows primarily focus on performance improvements without considering energy constraints, resulting in significant energy consumption during model use and a significant impact on the environment.

[0082] AI refers to the ability to imbue machines with human intelligence, such as enabling them to use computer hardware and software to simulate certain intelligent human behaviors. To implement AI, ML methods can be employed, such as using training data to learn or train an ML model (i.e., model training). The model generated through model training can represent the mapping between input data and output data and can be used for inference (i.e., model reasoning). In other words, the model can be used to obtain output data corresponding to given input data. It is understood that the model generated through model training can be an AI model, an ML model, or other model, and an AI model can include an ML model, meaning that an ML model is a type of AI model. An AI model can be considered a specific method for implementing an AI function, representing a mapping relationship or function between the input and output of the AI ​​model. This AI function, also known as an AI operation, can include at least one of the following: data collection, model training, model learning, model information publishing, model inference, model reasoning, or model prediction.

[0083] Currently, energy consumption during model use can be reduced through model lightweighting. Model lightweighting technology is a technique that reduces the number of model parameters while ensuring the necessary accuracy. It includes methods such as pruning, quantization, and distillation. Model pruning removes "unimportant" weights from the model, reducing the number of model parameters and computational complexity while minimizing the impact on model accuracy. Model quantization is the process of converting trained model parameters from high-precision to low-precision, which can effectively reduce the model's computational overhead, parameter size, and memory consumption. Model distillation involves transferring knowledge from a complex model to a simpler, smaller model, so that the performance of the simpler model approaches or exceeds that of the complex model, thereby achieving similar prediction results with less complexity. Model lightweighting can reduce model computational overhead and, in turn, the energy consumption of model inference.

[0084] However, lightweighting technology can only reduce computational energy consumption by reducing the number of model parameters. To ensure model accuracy, the number of model parameters can only be reduced to a small extent. The actual factors affecting model inference energy consumption are not only the model itself, but also the hardware capabilities and the number of inferences. For example, an experiment comparing the energy consumption of the GShard model and the GPT-3 model showed that GShard, with its 619 billion parameters, actually consumed approximately 53 times less energy and had approximately 127 times lower net carbon emissions than GPT-3, with its 175 billion parameters. This is primarily due to GShard's multiple optimizations in both the algorithm and hardware. In other words, model lightweighting technology, which reduces computational energy consumption by reducing the number of model parameters, has a very limited impact on energy consumption. Even with model lightweighting technology, model inference energy consumption remains high, and the energy efficiency of model inference is low.

[0085] To address the above technical issues, the present invention provides a communication method. Considering that the energy consumption of model inference can be estimated by multiplying the energy consumption of a single inference by the number of inferences, the present invention improves the energy efficiency of model inference from two aspects: the energy consumption of a single inference and the number of inferences: 1. By exchanging transmission resources for energy efficiency, hardware energy efficiency information for different inference locations is obtained, and the deployment location with the best energy efficiency is selected to perform inference. 2. By exchanging storage resources for energy efficiency, historical inference results are stored. When the input data deviation is less than a set threshold, the historical inference results are directly used instead, reducing the number of inference executions.

[0086] The communication method and communication system provided in the embodiments of the present application are described below in conjunction with the accompanying drawings.

[0087] The communication method provided in the embodiments of the present application can be applied to various communication systems, such as: sixth-generation (6G) mobile communication systems, long-term evolution (LTE) systems, fifth-generation (5G) mobile communication systems, wireless fidelity (WiFi) systems, future communication systems, or systems integrating multiple communication systems, etc., and the embodiments of the present application are not limited thereto. 5G can also be referred to as new radio (NR).

[0088] The network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field will know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0089] As shown in Figure 2, a schematic diagram of the architecture of a communication system provided in an embodiment of the present application is shown. As shown in Figure 2, the communication system 20 includes a first node 210 and a second node 220. Optionally, as shown in Figure 2, the communication system also includes at least one third node 230.

[0090] The first node 210 is used to send first information to the second node 220 , where the first information is used to query the processing capability and / or energy supply information of at least one third node 230 .

[0091] The second node 220 is configured to receive the first information and send second information to the first node 210 , where the second information indicates the processing capability and / or power supply information of the at least one third node 230 .

[0092] The first node 210 is further configured to receive the second information and determine at least one target third node 230 for executing the task based on the second information.

[0093] Optionally, in the embodiments of the present application, the first node may be, for example, a model loading consumer (ML loading consumer), the second node may be, for example, a model loading producer (ML loading producer), and the third node may be, for example, a model inference (ML inference) device. The following describes several possible application architectures based on different scenarios.

[0094] Figure 3 is a schematic diagram of a communication architecture provided by an embodiment of the present application. As shown in Figure 3, the communication architecture includes a network management system (NMS), an element management system (EMS), and a radio access network (RAN) device.

[0095] Among them, NMS is responsible for the operation, management and maintenance functions of the network, and can also be called a cross-domain management system.

[0096] The EMS is used to manage one or more network elements of a certain category and may also be called a domain management system or a single domain management system.

[0097] RAN equipment is a device in a mobile communication system that connects the fixed part and the wireless part and is connected to mobile terminals through wireless channels in the air. Figure 3 uses the RAN equipment as an example of a next-generation base station (gNB).

[0098] The NMS acts as a model loading consumer, while the EMS provides model loading services as a model loading producer. The gNB has model inference (ML inference), responsible for model inference, inputting data into the model and obtaining the corresponding output. The NMS can invoke the model loading service provided by the EMS to instruct the loading of a model into a specific gNB.

[0099] In addition, the embodiments of the present application are also applicable to the O-RAN architecture or the mobile intelligent function (MIF) architecture.

[0100] O-RAN aims to realize an intelligent and open access network. O-RAN is based on the concepts of RAN interoperability and standardization, providing unified interconnection standards for white box hardware and software from different vendors.

[0101] As shown in Figure 4, in a possible O-RAN architecture, the NMS is implemented as a service management and orchestration framework (SMO), and the non-RT RIC belongs to the SMO and acts as an ML loading consumer. RAN equipment is divided into multiple logical network elements, including the O-CU, O-DU, and O-RU modules. O-RAN does not have an EMS; the network element that implements the EMS function is the Near-RT RIC. The Near-RT RIC provides both ML loading producer and ML inference. Specifically, the Non-RT RIC acts as an ML loading consumer, the Near-RT RIC acts as an ML loading producer, and ML inference is deployed in the Near-RT RIC. There are multiple Near-RT RICs. The Non-RT RIC can select a model deployment location based on the Near-RT RIC's inference hardware energy efficiency information, aiming for maximum energy efficiency and minimum carbon emissions.

[0102] Alternatively, as shown in Figure 5, in another possible O-RAN architecture, the Near-RT RIC provides the ML loading producer, while any one of the O-CU, O-DU, and O-RU modules provides ML inference. Specifically, the Non-RT RIC acts as the ML loading consumer, the Near-RT RIC acts as the ML loading producer, and ML inference is deployed in the O-CU / O-DU / O-RU, where there are multiple O-CU / O-DU / O-RUs. The Non-RT RIC can select the model deployment location based on the energy efficiency information of the inference hardware of the O-CU / O-DU / O-RU, with the goal of maximizing energy efficiency and minimizing carbon emissions.

[0103] The MIF is the AI ​​intelligent service processing logic entity of the RAN network, implementing intelligent data analysis in the RAN domain. The MIF connects to the gNB via the G1 interface. The MIF implements AI model-related functions such as model training and evaluation.

[0104] As shown in Figure 6, in a possible MIF architecture, the MIF acts as the ML loading consumer, and the CU / DU in the gNB acts as the ML loading producer. ML inference is also deployed in the CU / DU, allowing a single MIF to manage multiple gNBs. The MIF can select the model deployment location for maximum energy efficiency and minimum carbon emissions based on the CU / DU's inference hardware energy efficiency information.

[0105] Alternatively, as shown in Figure 7, in another possible MIF architecture, the MIF serves as the ML loading consumer, the CU serves as the ML loading producer, and ML inference is deployed in the DU. A single CU supports multiple DUs. MIF can select the model deployment location based on the DU's inference hardware energy efficiency information, aiming for maximum energy efficiency and minimum carbon emissions.

[0106] It should be understood that the network elements responsible for the ML loading consumer, ML loading producer, and ML inference in the above examples are merely illustrative. In actual implementation, based on differences in network architecture, the network elements responsible for the above roles may also have other designs, which are not limited.

[0107] The communication method provided in the embodiment of the present application is described below in conjunction with the communication systems shown in Figures 2 to 7.

[0108] It should be noted that in the following embodiments of the present application, the message names, parameter names, or information names between network elements are only examples. In other embodiments, they may also be other names. The communication method provided in this application does not make specific limitations on this.

[0109] It is understood that in the embodiments of the present application, each network element may perform some or all of the steps in the embodiments of the present application. These steps or operations are merely examples, and the embodiments of the present application may also perform other operations or variations of various operations. In addition, the steps may be performed in a different order than those presented in the embodiments of the present application, and it is possible that not all operations in the embodiments of the present application need to be performed.

[0110] Figure 8 is an example of a communication method provided in an embodiment of the present application. The method is illustrated by taking the interaction between a first node and a second node as an example. Of course, the subject that executes the action of the first node in the method can also be a device / module in the first node, such as a chip, processor, processing unit, etc. in the first node; the subject that executes the action of the second node in the method can also be a device / module in the second node, such as a chip, processor, processing unit, etc. in the second node, and the embodiment of the present application does not make specific limitations on this. The processing performed by a single execution subject (for example, a first node or a second node) in the embodiment of the present application can also be divided into executions by multiple execution subjects, and these execution subjects can be logically and / or physically separated. Exemplarily, as shown in Figure 8, the method may include the following steps:

[0111] S810: A first node sends first information to a second node. Correspondingly, the second node receives the first information.

[0112] The first information is used to query the processing capability and / or energy supply information of at least one third node. The processing capability includes at least one of the following: hardware processing capability, storage capability, and hardware energy efficiency information.

[0113] In an embodiment of the present application, the hardware processing capability and storage capability can be used to determine whether the third node can meet the task requirements in combination with the model parameter quantity. The hardware processing capability and hardware energy efficiency information can be used to determine the energy consumption required to perform the task. Exemplarily, the hardware energy efficiency information includes at least one of the following: average processor power (the average power of the processor when it is running, which can be obtained by measurement), or power usage efficiency (the percentage of the power consumed by the processor that is used for calculation).

[0114] In this embodiment of the present application, the energy supply information includes an indication of the energy type used to power the third node. For example, the energy type can be divided into green energy and non-green energy. Due to factors such as natural conditions, green energy is generally not available 24 / 7, but has a specific energy availability period, while non-green energy is generally available 24 / 7.

[0115] Optionally, in an embodiment of the present application, the energy supply information may also include the corresponding energy available time, the carbon emissions per unit of energy, etc., which is not specifically limited in the embodiment of the present application.

[0116] Optionally, the first information is also used to indicate range information of the third node to be queried. The range information indicates the geographical range of the third node to be queried. By limiting the query to third nodes within a certain range, subsequent transmission overhead can be reduced.

[0117] S820: The second node sends second information to the first node. Correspondingly, the first node receives the second information.

[0118] The second information indicates processing capability and / or power supply information of at least one third node.

[0119] Optionally, in an embodiment of the present application, the second information includes identification information of the third node and corresponding processing capability and / or power supply information.

[0120] Optionally, in an embodiment of the present application, the second information may further indicate range information of at least one third node.

[0121] Optionally, in an embodiment of the present application, the second node can obtain the above-mentioned second information from at least one third node.

[0122] S830: The first node determines at least one target third node for executing the task according to the second information.

[0123] Optionally, the task in the embodiment of the present application can be at least one of model training, model testing, model simulation, model loading, or model reasoning. After receiving the second information, the first node can select one or more third nodes with green energy supply, low energy consumption and meeting the model task requirements as the target third node to perform the task by comparing the processing capabilities and / or energy supply information of each third node. In other words, the energy consumption of the target third node is lower than that of at least one third node and / or the energy type of the energy supply of the target third node is green energy.

[0124] In one embodiment, if there are multiple target third nodes determined, the target third nodes for executing the task can be determined by time period. For example, the target third nodes include node A and node B, then node A can be determined to execute the task from 00:00 to 12:00, and node B can be determined to execute the task from 12:00 to 24:00. For another example, if target third node 1 has green energy available and there is no time limit, then the target third node that actually executes the task is target third node 1, and the execution time period may not be indicated (the default is no time limit); in another case, target third node 1 has green energy available, and the available time period is from 10 am to 4 pm a day, and target third node 2 also has green energy available, and the available time period is from midnight to 10 am and from 4 pm to 12 am a day, then the target third nodes that actually execute the task are determined to be target third node 1 and target third node 2, and the execution time period of target third node 1 is from 10 am to 2 pm. In the afternoon, the execution period of target third node 2 is from midnight to ten in the morning and from four in the afternoon to twelve in the morning. In another case, target third node 1 has green energy available, and the available time is from ten in the morning to four in the afternoon of the same day. Other target third nodes have no green energy available. Then the target third nodes that actually execute the task are determined to be target third node 1 and target third node 2, among which target third node 2 is the target third node with the lowest energy consumption for a single task. The execution period of target third node 1 is from ten in the morning to four in the afternoon, and the execution period of target third node 2 is from midnight to ten in the morning and from four in the afternoon to twelve in the morning.

[0125] It should be understood that the above description uses two target third nodes as an example. In actual implementation, the number of target third nodes can also be multiple, and the embodiments of the present application do not limit this.

[0126] In one embodiment, the first information is used to query the processing capability of at least one third node, and accordingly, the second information includes identification information and corresponding processing capability of the third node, which is used to indicate the processing capability of at least one third node. In an embodiment of the present application, the first node can estimate the energy consumption of executing the task. For example, the energy consumption of a single inference = the execution time of a single inference × the average power of the processor × the efficiency of electric energy use. Among them, the execution time of a single inference = the amount of calculation of a single inference / the processing speed, and the processing speed depends on the hardware processing capability. The stronger the hardware processing capability, the faster the processing speed. Through the above principle, after obtaining the hardware processing capability of at least one third node, the first node can determine the single inference energy consumption of at least one third node according to the hardware processing capability of at least one third node, and then select one or more third nodes with lower energy consumption as the target third node for executing the task.

[0127] In one embodiment, the first information is used to query the energy supply information of at least one third node. Accordingly, the second information includes identification information of the third node and corresponding energy supply information, and is used to indicate the energy supply information of the at least one third node. In this embodiment of the present application, the first node can determine the energy type used to power each third node based on the energy type in the energy supply information, and then select one or more third nodes powered by green energy as the target third nodes for executing the task.

[0128] Optionally, if the energy supply information also includes the energy available time corresponding to the energy type, the target third node that performs the task in each time period can be determined based on the energy available time. That is, the first node can determine the time for each target third node to perform the task based on the energy supply information in the second information. For example, the target third nodes include node A and node B, and the energy available time of node A is 00:00-12:00, and the energy available time of node B is 12:00-24:00, then the first node can determine that node A performs the task from 00:00-12:00, and node B performs the task from 12:00-24:00.

[0129] In another embodiment, the first information is used to query the processing capabilities and energy supply information of at least one third node. Accordingly, the second information includes the identification information of the third node and the corresponding processing capabilities and energy supply information. In this case, the target third node for executing the task can be determined by comprehensively considering the energy supply type and energy consumption.

[0130] Exemplarily, the first node may preferentially determine a candidate third node powered by green energy based on the energy supply information, and then determine one or more candidate third nodes with lower energy consumption as the target third nodes for executing the task based on the processing capabilities of the candidate third nodes.

[0131] For another example, the first node can estimate the carbon emissions of a single inference based on processing power and energy supply information, and select one or more third nodes with lower carbon emissions as target third nodes. Here, the carbon emissions of a single inference (estimated) = single inference execution time × average processor power × power efficiency × carbon emissions per unit energy (indicated by energy supply information). Here, the execution time of a single inference = single inference computational effort / processing speed.

[0132] In another example, the first node can score at least one third node based on the energy supply type determined by the energy supply information and the energy consumption determined by the processing capacity, and take one or more third nodes with higher scores as the target third nodes for executing the task. For example, the green energy score is +8 points, the non-green energy score is +4 points, and the scoring rule for the energy consumption value is to take the reciprocal of the energy consumption value and then multiply it by the common multiplier as the score. For example, the single inference energy consumption of the third node is 25 (this is a principle explanation and does not limit the energy consumption unit), then the reciprocal of 25 is 0.04, the common multiplier is 100, and the score is +4. Assuming that the energy score of the third node A is +8 and the energy consumption score is +1, the final score of the third node A is +9. Assuming that the energy score of the third node B is +4 and the energy consumption score is +4, the final score of the third node A is +8. Between the third node A and the third node B, the third node A is preferentially selected as the target third node.

[0133] In another embodiment, in addition to querying the processing capability and / or energy supply information of the third node, the first information is also used to specify the range information of the third node that needs to be queried. Accordingly, the second information includes the identification information, range information and at least one of the following items of the third node: processing capability and energy supply information. At this time, the first node can preferentially determine the third node within a certain range as the candidate third node based on the range information, and then select the target third node from the candidate third nodes based on the processing capability and / or energy supply information. The determination rule of the "certain range" can be set flexibly. For example, all places that are less than a preset distance threshold from the second node belong to the "certain range", or all places that are less than a preset distance threshold from the third node for which the execution result of the task needs to be obtained belong to the "certain range", etc. The embodiment of the present application does not make specific restrictions on this. Among them, determining the target third node based on the range information of the third node can ensure that the transmission overhead is small.

[0134] In an embodiment of the present application, the first node first queries the processing capacity and / or energy supply information of the third node, and determines the target third node for performing the task based on the processing capacity and / or energy supply information of the third node, so that the selected target third node can have lower energy consumption (and / or lower carbon emissions) when performing the task, thereby improving the energy efficiency during the task execution process.

[0135] In one embodiment, as shown in FIG9 , the communication method provided in the embodiment of the present application further includes the following steps S840 to S890:

[0136] S840: The first node sends third information to the second node, and correspondingly, the second node receives the third information.

[0137] The third information is used to indicate a third node that needs to obtain the execution result of the task (hereinafter referred to as the required third node) and at least one target third node.

[0138] Optionally, the third information may also be used to indicate a task that needs to be performed.

[0139] Exemplarily, the third information includes identification information of the requesting third node and identification information of at least one target third node. Optionally, the third information also includes identification information or description information of a task to be performed.

[0140] Optionally, when there are multiple target third nodes, the third information may also be used to indicate the time for each target third node to execute the task.

[0141] S850: The second node sends fourth information to the target third node. Correspondingly, the target third node receives the fourth information.

[0142] The fourth information is used to indicate that the third node is required.

[0143] Optionally, the fourth information may also be used to indicate a task that needs to be performed.

[0144] In the embodiment of the present application, the target third node can determine which third node the required third node is based on the fourth information.

[0145] Optionally, in an embodiment of the present application, the target third node may also determine a model for executing the task based on the indicated task.

[0146] S860, the second node sends fifth information to the requesting third node, and correspondingly, the requesting third node receives the fifth information.

[0147] The fifth information is used to indicate the target third node.

[0148] Optionally, the fifth information may also be used to indicate a task that needs to be performed.

[0149] Optionally, when there are multiple target third nodes, the fifth information can also be used to indicate the time for each target third node to execute the task.

[0150] S870, the demanding third node sends the task parameters required for executing the task to the target third node, and correspondingly, the target third node sends the task parameters required for executing the task.

[0151] The demanding third node determines the third node that performs the task (ie, the target third node) based on the fifth information in S860, and sends the task parameters required for performing the task to the target third node based on the fifth information.

[0152] S880: The target third node executes the task according to the task parameters and obtains the execution result of the task.

[0153] Among them, after receiving the task parameters, the target third node can execute the task according to them and obtain the execution result of the task.

[0154] S890, the target third node sends the execution result of the task to the demand third node, and correspondingly, the demand third node receives the execution result of the task.

[0155] Among them, the demand third node receives the execution result of the task, which means that the task requirement of the demand third node is realized.

[0156] Optionally, in an embodiment of the present application, when there are multiple target third nodes (that is, the fifth information also indicates the time for each target third node to perform the task), the demand third node can send task parameters to the corresponding target third nodes at different times of performing the task. For example, the target third node includes a target third node A and a target third node B, and the time for performing the task corresponding to the target third node A and the target third node B is time period 1 and time period 2, respectively. Then the demand third node sends the task parameters to the target third node A in time period 1, and sends the task parameters to the target third node B in time period 2. Accordingly, the target third node A performs the task according to the received task parameters in time period 1, obtains the execution result of the task and feeds it back to the demand third node in time period 1; the target third node B performs the task according to the received task parameters in time period 2, obtains the execution result of the task and feeds it back to the demand third node in time period 2.

[0157] In an embodiment of the present application, the target third node executes the task according to the task parameters and sends the execution result of the task to the demand third node. Since the target third node has lower energy consumption (and / or lower carbon emissions) in executing the task, the energy efficiency in the task execution process is improved.

[0158] In one embodiment, as shown in FIG10 , the communication method provided in the embodiment of the present application further includes the following steps S1001 to S1003:

[0159] S1001: A first node sends sixth information to a second node, and correspondingly, the second node receives the sixth information.

[0160] Among them, the sixth information indicates the historical processing result of the calling task.

[0161] Optionally, the sixth information may further indicate a data deviation threshold used to determine whether the historical processing result of the task is usable.

[0162] In embodiments of the present application, the first node can flexibly design scenarios that trigger the sending of the sixth information. For example, if the first node finds a high degree of data similarity between historical tasks and tasks within the current region / time period, the sending of the sixth information is triggered. Alternatively, a data deviation threshold can be determined based on the similarity of the historical data.

[0163] S1002: The second node sends sixth information to the target third node. Correspondingly, the target third node receives the sixth information.

[0164] The target third node (ie, the third node that executes the task) stores historical task parameters and corresponding historical processing results.

[0165] S1003: The target third node determines the target historical processing result as the execution result of the task.

[0166] Among them, in the embodiment of the present application, the historical task parameters corresponding to the target historical processing results match the current task parameters. In other words, the data difference between the historical task parameters corresponding to the target historical processing results and the current task parameters is less than the data deviation threshold.

[0167] In the embodiment of the present application, using historical processing results to replace the actual task execution process can reduce the computing power required to execute the task, thereby improving the energy efficiency during the task execution process.

[0168] In one embodiment, optionally, as shown in FIG11 , the communication method provided in the embodiment of the present application further includes the following steps S1004 to S1006:

[0169] S1004: The first node sends seventh information to the second node, and correspondingly, the second node receives the seventh information.

[0170] The seventh information is used to indicate the storage of historical processing results.

[0171] Optionally, the seventh information is also used to indicate the time and / or area for storing the execution history processing results.

[0172] S1005: The second node sends seventh information to the target third node. Correspondingly, the target third node receives the seventh information.

[0173] S1006: The target third node stores the task parameters of the historical task and the corresponding historical processing results according to the seventh information.

[0174] The task parameters of the historical tasks and the corresponding historical processing results stored in the target third node may be used to determine the execution result in step S1003 .

[0175] Combining the above embodiments, it can be seen that the present embodiment improves the energy efficiency of task execution by selecting a third node with lower energy consumption and / or lower carbon emissions to execute the task. In addition, the present embodiment designs a mechanism for replacing the processing result of the current task with the historical processing result, further reducing the number of necessary executions, thereby further improving the energy efficiency of task execution.

[0176] Below, taking the communication system shown in Figure 2 applicable to the communication architecture shown in Figure 3 as an example, combined with the embodiments described in Figures 8 to 11, several communication methods provided in the embodiments of the present application are given, as shown in Figures 12 to 14 respectively.

[0177] In one possible implementation, the solution trades transmission resources for energy efficiency. By obtaining hardware energy efficiency information at different inference locations, the deployment location with the best energy efficiency is selected for inference execution. As shown in FIG12 , the communication method includes the following steps:

[0178] S1210: The NMS sends a query request message to the EMS, and the EMS receives the query request message accordingly.

[0179] The query request message includes first information, and the first information is used to query the processing capability of at least one gNB.

[0180] In the embodiment of the present application, the processing capability includes, for example, at least one of the following: hardware processing capability, storage capability, hardware energy efficiency information, or range information. For a description of the processing capability, reference may be made to the relevant content in step S810 of the embodiment described in FIG8 , and will not be repeated here.

[0181] In an embodiment of the present application, the first information may include, for example, at least one of the following: information used to indicate the hardware processing capability of the queried gNB, information used to indicate the storage capability of the queried gNB, information used to indicate the hardware energy efficiency information of the queried gNB, and information used to indicate the range information of the queried gNB.

[0182] S1220, the EMS sends a query response message to the NMS, and correspondingly, the NMS receives the query response message.

[0183] The query response message includes second information, and the second information indicates the processing capability of at least one gNB.

[0184] In this embodiment of the present application, the second information may include, for example, identification information of at least one gNB and at least one of the following: hardware processing capability of at least one gNB, storage capability of at least one gNB, or hardware energy efficiency information of at least one gNB. It is understood that the type of information included in the second information depends on the query content of the first information. For example, if the first information is used to query information about the hardware processing capability of the gNB, the second information includes the identification information of the gNB and the corresponding hardware processing capability information. For another example, if the first information is used to query information about the hardware processing capability and hardware energy efficiency of the gNB, the second information includes the identification information of the gNB, the corresponding hardware processing capability information, and the corresponding hardware energy efficiency information.

[0185] For the relevant description of the second information, please refer to the relevant content in step S820 in the embodiment described in FIG8 , which will not be repeated here.

[0186] In one possible implementation, in an embodiment of the present application, the EMS may store the processing capabilities of at least one gNB. In this case, after receiving the query request message, the EMS may send a query response message to the NMS.

[0187] In another possible implementation, in an embodiment of the present application, the EMS does not store the processing capabilities of at least one gNB. In this case, after receiving the query request message, the EMS needs to query the processing capabilities of the at least one gNB. For example, as shown in Figure 12, the following steps are included: S1201: The EMS sends a query request message to at least one gNB (e.g., including a target gNB, a requesting gNB, and other gNBs). In response, the at least one gNB receives the query request message from the EMS. S1202: The at least one gNB sends a query response message to the EMS. In response, the EMS receives a query response message from the at least one gNB. For a description of the query request message and query response message, refer to steps S1210 and S1220 and are not repeated here.

[0188] It should be noted that the query response message in step S1202 indicates the processing capabilities of the gNB that replied to the query response message. The processing capabilities of one or more gNBs indicated in the query response message in step S1220 are uniformly described here and are not further described below. For example, the second information in the query response message replied by the target gNB to the EMS indicates the processing capabilities of the target gNB, the second information in the query response message replied by the demanding gNB to the EMS indicates the processing capabilities of the demanding gNB, and the second information in the query response message replied by other gNBs to the EMS indicates the processing capabilities of other gNBs; the second information in the query response message replied by the EMS to the NMS indicates the processing capabilities of the target gNB, the processing capabilities of the demanding gNB, and the processing capabilities of other gNBs.

[0189] It should be understood that the target gNB is the gNB used to execute the task, the required gNB is the gNB that needs to obtain the execution result of the task, and other gNBs are gNBs other than the target gNB and the required gNB, and are queried by the query request message in S1210.

[0190] S1230: The NMS determines at least one target gNB for performing the task based on the query response message.

[0191] Among them, the description of how the NMS determines at least one target gNB for performing the task based on the query response message can refer to the relevant content in step S830 in the embodiment described in Figure 8, and will not be repeated here.

[0192] S1240 , the NMS sends a task request message 1 to the EMS. Correspondingly, the EMS receives the task request message 1 from the NMS.

[0193] The task request message 1 includes third information, which indicates the requesting gNB and at least one target gNB (Figure 12 uses one target gNB as an example). Optionally, the third information may also indicate the task. In this embodiment, gNBs other than the requesting gNB and the target gNB are referred to as other gNBs.

[0194] In this embodiment of the present application, the third information may include, for example, task identification information, identification information of the requesting gNB, and identification information of the target gNB. For example, if the task is model loading, the task identification information is the model identification information, and the aforementioned task request message 1 may be replaced with model loading request 1. For a description of the third information, please refer to the relevant content in step S840 of the embodiment described in FIG. 9 and will not be repeated here.

[0195] S1250: The EMS sends a task request message 2 to the target gNB. In response, the target gNB receives the task request message 2 from the EMS.

[0196] Task Request Message 2 includes fourth information, which includes identification information of the requesting gNB. Optionally, the fourth information may also include identification information of the task. For example, if the task is model loading, the identification information of the task is model identification information, and Task Request Message 2 may be replaced with Model Load Request Message 2. For a description of the fourth information, refer to step S850 in the embodiment described in FIG. 9 and will not be repeated here.

[0197] S1260: The EMS sends a task notification message to the requesting gNB. Correspondingly, the requesting gNB receives the task notification message from the EMS.

[0198] The task notification message includes fifth information, which includes identification information of the target gNB. Optionally, the fifth information may also include identification information of the task. For example, if the task is model loading, the identification information of the task is model identification information, and the task notification message may be replaced with a model loading notification. For a description of the fifth information, refer to the relevant content in step S860 of the embodiment described in FIG. 9 and will not be repeated here.

[0199] S1270: The demanding gNB sends a task request message 3 to the target gNB. Correspondingly, the target gNB receives the task request message 3 from the demanding gNB.

[0200] The task request message 3 includes the task parameters required for executing the task. For example, if the task is model inference, the task request message 3 can be replaced with a model inference request. For a description of the task parameters required for executing the task, refer to the relevant content in step S870 of the embodiment described in FIG. 9 , and will not be repeated here.

[0201] S1280: The target gNB executes the task according to task request message 3 and obtains the task execution result.

[0202] After receiving the task parameters in Task Request Message 3, the target gNB executes the task accordingly and obtains the task execution result. For a related description, please refer to step S880 in the embodiment described in FIG9 , and will not be repeated here.

[0203] S1290: The target gNB sends the task execution result to the requesting gNB. Correspondingly, the requesting gNB receives the task execution result.

[0204] For example, when the task is model reasoning, the execution result of the above task can also be replaced by the model reasoning result. The description of the execution result of the task can refer to the relevant content of step S890 in the embodiment described in Figure 9, which will not be repeated here.

[0205] In another possible implementation, similar to the embodiment described in FIG12 , this solution exchanges transmission resources for energy efficiency, and by obtaining hardware energy efficiency information of different inference locations, selects the deployment location with the best energy efficiency to perform inference. Compared with the embodiment described in FIG12 , the difference is, for example, that in this implementation, in a scenario where green energy is used, the hardware processing capacity and green energy resource information of different inference locations can be obtained to select the deployment location with the lowest carbon emissions to perform inference. As shown in FIG13 , taking the example of the target third node including the target gNB1 and the target gNB2, where the energy type supplied by the target gNB1 is green energy and the energy type supplied by the target gNB2 is non-green energy, the communication method includes the following steps:

[0206] S1310: The NMS sends a query request message to the EMS, and the EMS receives the query request message accordingly.

[0207] The query request message includes first information, and the first information is used to query the processing capability and power supply information of at least one gNB.

[0208] In the embodiment of the present application, processing capability includes, for example, at least one of the following: hardware processing capability, storage capability, hardware energy efficiency information, or range information. Energy supply information includes energy type and, optionally, energy availability time and / or carbon emissions per unit of energy. For further information on processing capability and energy supply information, please refer to step S810 in the embodiment described in FIG8 and will not be repeated here.

[0209] In an embodiment of the present application, the first information may include, for example, at least one of the following: information used to indicate the hardware processing capability of the gNB to be queried, information used to indicate the storage capability of the gNB to be queried, information used to indicate the hardware energy efficiency information of the gNB to be queried, or information used to indicate the range information of the gNB to be queried; and the first information includes information for querying the energy type of the gNB.

[0210] S1320, the EMS sends a query response message to the NMS, and correspondingly, the NMS receives the query response message.

[0211] The query response message includes second information, and the second information indicates the processing capability and power supply information of at least one gNB.

[0212] In this embodiment of the present application, the second information may include, for example, identification information of at least one gNB and at least one of the following: the energy supply type of at least one gNB, the energy availability time of at least one gNB, the hardware processing capability of at least one gNB, the storage capability of at least one gNB, or the hardware energy efficiency information of at least one gNB. It is understood that the type of information included in the second information depends on the query content of the first information. For example, if the first information is used to query the hardware processing capability information of the gNB, the second information includes the identification information of the gNB and the corresponding hardware processing capability information. For another example, if the first information is used to query the hardware processing capability information and hardware energy efficiency information of the gNB, the second information includes the identification information of the gNB, the corresponding hardware processing capability information, and the corresponding hardware energy efficiency information. For another example, if the first information is used to query the hardware processing capability information, energy supply type, and hardware energy efficiency information of the gNB, the second information includes the identification information of the gNB, the corresponding hardware processing capability information, the corresponding energy supply type, and the corresponding hardware energy efficiency information.

[0213] For the relevant description of the second information, please refer to the relevant content in step S820 in the embodiment described in FIG8 , which will not be repeated here.

[0214] In one possible implementation, in an embodiment of the present application, the EMS may store processing capability and energy supply information of at least one gNB. In this case, after receiving the query request message, the EMS may send a query response message to the NMS.

[0215] In another possible implementation, in an embodiment of the present application, the EMS does not store the processing capability and energy supply information of at least one gNB. In this case, after receiving the query request message, the EMS needs to query the processing capability and energy supply information of the at least one gNB from the at least one gNB. For example, as shown in Figure 13, the following steps are included: S1301: The EMS sends a query request message to at least one gNB (e.g., including a target gNB, a requesting gNB, and other gNBs). In response, the at least one gNB receives the query request message from the EMS. S1302: The at least one gNB sends a query response message to the EMS. In response, the EMS receives a query response message from the at least one gNB. For a description of the query request message and the query response message, refer to steps S1310 and S1320 and are not repeated here.

[0216] It should be noted that the query response message in step S1302 indicates the processing capability and energy supply information of the gNB that replied to the query response message. The query response message in step S1320 indicates the processing capability and energy supply information of one or more gNBs. For example, the second information in the query response message replied by the target gNB to the EMS indicates the processing capability and energy supply information of the target gNB, the second information in the query response message replied by the demand gNB to the EMS indicates the processing capability and energy supply information of the demand gNB, and the second information in the query response message replied by other gNBs to the EMS indicates the processing capability and energy supply information of other gNBs; the second information in the query response message replied by the EMS to the NMS indicates the processing capability and energy supply information of the target gNB, the processing capability and energy supply information of the demand gNB, and the processing capability and energy supply information of other gNBs.

[0217] S1330: The NMS determines at least one target gNB for performing the task based on the query response message.

[0218] Among them, the NMS selects at least one gNB with the lowest carbon emissions as the target gNB based on the processing capacity and energy supply information of each gNB in ​​the query response message. If there are multiple target gNBs and the energy supply information also includes the energy availability time corresponding to the energy type, the target gNB powered by green energy in each time period can be determined based on the energy availability time to perform the task.

[0219] For example, in this embodiment, the target gNBs include target gNB1 and target gNB2. Target gNB1 is powered by green energy, while target gNB2 is powered by non-green energy. The task execution time corresponding to target gNB1 is time period 1, while the task execution time corresponding to target gNB2 is a time period outside time period 1 (e.g., time period 2).

[0220] For an explanation of how the NMS determines at least one target gNB for performing the task based on the query response message, please refer to the relevant content in step S830 of the embodiment described in Figure 8, and will not be repeated here.

[0221] S1340 , the NMS sends a task request message 1 to the EMS. Correspondingly, the EMS receives the task request message 1 from the NMS.

[0222] Task Request Message 1 includes third information, which indicates the requesting gNB and at least one target gNB (e.g., target gNB1 and target gNB2 in Figure 13 ). Optionally, the third information may also indicate the task. In this embodiment, gNBs other than the requesting gNB and the target gNB are referred to as other gNBs. For a description of the third information, refer to step S1240 in the embodiment described in Figure 12 and are not repeated here.

[0223] S1350: The EMS sends a task request message 2 to the target gNB. In response, the target gNB receives the task request message 2 from the EMS.

[0224] Task Request Message 2 includes fourth information, which includes identification information of the requesting gNB. Optionally, the fourth information may also include identification information of the task. For an explanation of Task Request Message 2, refer to step S1250 in the embodiment described in FIG. 12 and are not further described here.

[0225] As mentioned above, there may be multiple target gNBs. In the embodiment of the present application, the target gNBs include target gNB1 and target gNB2. The EMS sends a task request message 2 to the target gNB1 and the target gNB2 respectively. Correspondingly, the target gNB1 and the target gNB2 receive the task request message 2 from the EMS.

[0226] S1360: The EMS sends a task notification message to the requesting gNB. Correspondingly, the requesting gNB receives the task notification message from the EMS.

[0227] The task notification message includes fifth information, which includes identification information of the target gNB (e.g., target gNB1 and target gNB2 in Figure 13 ). Optionally, the fifth information may also include identification information of the task. For a description of the task notification message, refer to step S1260 in the embodiment described in Figure 12 , and are not further described here.

[0228] In time period 1, the embodiment of the present application further includes the following steps S1370a-S1390a:

[0229] S1370a: The demand gNB sends a task request message 3 to the target gNB1 in time period 1. Correspondingly, the target gNB1 receives the task request message 3 from the demand gNB in ​​time period 1.

[0230] The task request message 3 includes the task parameters required for executing the task. For an explanation of the task request message 3, reference may be made to the relevant contents of step S1270 in the embodiment described in FIG12 , and no further details will be given here.

[0231] S1380a: Target gNB1 executes the task according to task request message 3 in time period 1 and obtains the task execution result.

[0232] After receiving the task parameters carried in Task Request Message 3, target gNB1 executes the task based on them and obtains the task execution result. For a related description, please refer to step S880 in the embodiment described in FIG8 , and will not be repeated here.

[0233] S1390a: The target gNB1 sends the task execution result to the demand gNB in ​​time period 1. Correspondingly, the demand gNB receives the task execution result from the target gNB1 in time period 1.

[0234] Among them, the relevant description of S1390 can refer to the relevant content of step S1290 in the embodiment described in Figure 12, and will not be repeated here.

[0235] Similarly, in time period 2, the embodiment of the present application further includes the following steps S1370b-S1390b:

[0236] S1370b: The demand gNB sends a task request message 3 to the target gNB2 in time period 2. Correspondingly, the target gNB2 receives the task request message 3 from the demand gNB in ​​time period 2.

[0237] S1380b: Target gNB2 executes the task according to task request message 3 in time period 2 and obtains the task execution result.

[0238] S1390b: The target gNB2 sends the task execution result to the demand gNB in ​​time period 2. Correspondingly, the demand gNB receives the task execution result from the target gNB2 in time period 2.

[0239] It should be understood that compared with S1370a-S1390a executed in time period 1, although the target gNB for implementing S1370b-S1390b ​​in time period 2 is changed from target gNB1 to target gNB2, the implementation principles of each step are the same. The relevant descriptions of each step in time period 2 can refer to the descriptions of the corresponding steps in time period 1 and will not be repeated here.

[0240] In another possible implementation, this solution trades storage resources for energy efficiency, stores historical inference results, and directly replaces them with historical inference results when the input data deviation is less than a set threshold, reducing the number of inference executions. As shown in Figure 14, this communication method may include:

[0241] S1410: The NMS sends a query request message to the EMS. Correspondingly, the EMS receives the query request message from the NMS.

[0242] Among them, the description of the query request message can refer to the description of step S1210 in Figure 12 or the description of step S1310 in Figure 13, which will not be repeated here.

[0243] S1420, the EMS sends a query response message to the NMS, and correspondingly, the NMS receives the query response message from the EMS.

[0244] Among them, the description of the query response message can refer to the description of step S1220 in Figure 12 or the description of step S1320 in Figure 13, which will not be repeated here.

[0245] Optionally, the communication method may further include: S1401, the EMS sending a query request message to at least one gNB (e.g., including a target gNB, a request gNB, and other gNBs). Accordingly, the at least one gNB receives the query request message from the EMS. S1402, the at least one gNB sending a query response message to the EMS. Accordingly, the EMS receives a query response message from the at least one gNB. For the description of S1401 and S1402, refer to the description of steps S1201 and S1202 in FIG. 12 or the description of steps S1301 and S1302 in FIG. These descriptions are not repeated here.

[0246] S1430: The NMS determines at least one target gNB for performing the task based on the query response message.

[0247] Among them, the relevant implementation of step S1430 can refer to the description of step S1230 in Figure 12 or step S1330 in Figure 13, which will not be repeated here.

[0248] S1440 , the NMS sends a task request message 1 to the EMS. Correspondingly, the EMS receives the task request message 1 from the NMS.

[0249] Among them, the task request message 1 includes third information and sixth information. Among them, the description of the third information can refer to the relevant content of step S1240 in the embodiment described in Figure 12, and will not be repeated here. The sixth information indicates the historical processing results of the calling task. Optionally, the sixth information can also indicate the data deviation threshold used to determine whether the historical processing results of the task are available. For example, the sixth information can include a data deviation threshold and a historical call indication message. The description of the sixth information can refer to the relevant description of step S1001 in Figure 10, and will not be repeated here.

[0250] The description of the task request message 1 may refer to step S1240 in FIG. 12 or step S1340 in FIG. 13 , and will not be repeated here.

[0251] S1450: The EMS sends a task request message 2 to the target gNB. In response, the target gNB receives the task request message 2 from the EMS.

[0252] The task request message 2 includes the sixth information and the fourth information. For an explanation of the sixth information, refer to the relevant description of S1440 and are not repeated here. For an explanation of the fourth information and the task request message 2, refer to step S1250 in FIG. 12 or step S1350 in FIG. 13 and are not repeated here.

[0253] S1460: The EMS sends a task notification message to the requesting gNB. Correspondingly, the requesting gNB receives the task notification message from the EMS.

[0254] Among them, the description of the task notification message can refer to the description of step S1260 in Figure 12 or the description of step S1360 in Figure 13, which will not be repeated here.

[0255] S1470: The demanding gNB sends a task execution request message 3 to the target gNB. Correspondingly, the target gNB receives the task request message 3 from the demanding gNB.

[0256] The description of the task request message 3 may refer to step S1270 in FIG. 12 or step S1370 in FIG. 13 , and will not be repeated here.

[0257] S1480: The target gNB determines the target historical processing result as the task execution result.

[0258] Among them, the data difference between the historical task parameters corresponding to the target historical processing result and the task parameters in the task request message 3 in S1470 is less than the data deviation threshold. The process of determining the execution result of the task can refer to the description of step S1003 in Figure 10 and will not be repeated here.

[0259] S1490: The target gNB sends the task execution result to the requesting gNB. Correspondingly, the requesting gNB receives the task execution result from the target gNB.

[0260] It should be understood that the message names in each step of Figures 12 to 14 are for exemplary introduction and may be other names in actual implementation without limitation.

[0261] Optionally, the embodiment of the present application may also use the communication system shown in FIG2 in the communication architecture shown in FIG4-FIG7 , and the interaction process related to the communication method of the embodiment of the present application may refer to the embodiment described in FIG12 to FIG14 . Compared with the embodiment shown in FIG12 , FIG13 , or FIG14 , the difference is that in this embodiment, the execution subject of each step in the embodiment described in FIG12 to FIG14 has changed, which is explained below with examples.

[0262] Exemplarily, when the communication system shown in Figure 2 is used in the communication architecture shown in Figure 4, the first node in the embodiments described in Figures 8 to 11 can be a Non-RT RIC, and the steps performed by the first node are performed by the Non-RT RIC, and the second node and the third node are both Near-RT RICs, and the steps performed by the second node and the third node are performed by the Near-RT RIC.

[0263] In another example, when the communication system shown in Figure 2 is used for the communication architecture shown in Figure 5, the first node in the embodiments described in Figures 8 to 11 may be a Non-RT RIC, and the Non-RT RIC executes the steps executed by the first node; the second node is a Near-RT RIC, and the Near-RT RIC executes the steps executed by the second node; the third node is an O-CU / O-DU / O-RU, and the O-CU / O-DU / O-RU executes the steps executed by the third node.

[0264] In another example, when the communication system shown in Figure 2 is used for the communication architecture shown in Figure 6, the first node in the embodiments described in Figures 8 to 11 may be a MIF, and the MIF performs the steps performed by the first node. The second node and the third node may both be CU / DU in the gNB, and the CU / DU in the gNB performs the steps performed by the second node and the third node.

[0265] In another example, when the communication system shown in Figure 2 is used for the communication architecture shown in Figure 7, the first node in the embodiments described in Figures 8 to 11 may be a MIF, and the MIF executes the steps executed by the first node; the second node is a CU in the gNB, and the CU in the gNB executes the steps executed by the second node; and the third node is a DU in the gNB, and the DU in the gNB executes the steps executed by the third node.

[0266] Combining the implementations of the above architectures, it can be seen that the embodiments of the present application improve the energy efficiency of task execution by selecting model inference nodes with lower energy consumption and / or lower carbon emissions to execute tasks. In addition, the embodiments of the present application design a mechanism for replacing the processing results of the current task with historical processing results, further reducing the number of necessary executions, thereby further improving the energy efficiency of task execution.

[0267] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the execution logic of each step. It is understandable that each node, such as the first node, includes a hardware structure and / or software module corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily appreciate that, in combination with the algorithm steps of each example described in the embodiment disclosed herein, the method of the embodiment of the present application can be implemented in the form of hardware, software, or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0268] In the embodiment of the present application, the functional modules of the first node can be divided according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. In actual implementation, there may be other division methods.

[0269] In a specific implementation, each node shown in this application may adopt the composition structure shown in Figure 15 or include the components shown in Figure 15. Figure 15 is a schematic diagram of the structure of a communication device provided in an embodiment of this application. When the communication device has the function of the first node described in an embodiment of this application, the communication device can be the first node or a chip or system-on-chip in the first node. When the communication device has the function of the second node described in an embodiment of this application, the communication device can be the second node or a chip or system-on-chip in the second node.

[0270] As shown in Figure 15 , the communication device may include a processor 1501, a communication line 1502, a transceiver 1503, and a memory 1504. The processor 1501, the memory 1504, and the transceiver 1503 may be connected via the communication line 1502. In one example, the processor 1501 may include one or more CPUs, such as CPU0 and CPU1 in Figure 15 .

[0271] As an optional implementation, the communication device includes multiple processors. For example, in addition to the processor 1501 in FIG. 15 , it may also include a processor 1507 .

[0272] The processor 1501 may be a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 1501 may also be other devices with processing functions, such as circuits, devices, or software modules.

[0273] The communication line 1502 is used to transmit information between the various components included in the communication device.

[0274] Transceiver 1503 is used to communicate with other devices or other communication networks. Such other communication networks may be Ethernet, radio access networks (RAN), wireless local area networks (WLAN), etc. Transceiver 1503 may be an interface circuit, a pin, a radio frequency module, a transceiver, or any other device capable of communication.

[0275] Furthermore, the communication device may further include a memory 1504. The memory 1504 is configured to store instructions, wherein the instructions may be computer programs.

[0276] Among them, the memory 1504 can be a read-only memory (ROM) or other types of static storage devices that can store static information and / or instructions, or a random access memory (RAM) or other types of dynamic storage devices that can store information and / or instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage, magnetic disk storage media or other magnetic storage devices, and optical disc storage includes compact disc, laser disc, optical disc, digital versatile disc, or Blu-ray disc, etc.

[0277] It should be noted that the memory 1504 can exist independently of the processor 1501 or can be integrated with the processor 1501. The memory 1504 can be used to store instructions, program code, or some data. The memory 1504 can be located inside the communication device or outside the communication device, without limitation. When the processor 1501 executes the instructions stored in the memory 1504, the method provided in the embodiment of the present application can be implemented.

[0278] As an optional implementation, the communication apparatus further includes an output device 1505 and an input device 1506. For example, the input device 1506 is a keyboard, a mouse, a microphone, a joystick, or the like, and the output device 1505 is a display screen, a speaker, or the like.

[0279] It should be noted that the communication device may be a desktop computer, a portable computer, a network server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device having a structure similar to that shown in FIG15 . Furthermore, the component structure shown in FIG15 does not limit the communication device. In addition to the components shown in FIG15 , the communication device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0280] In the embodiment of the present application, the chip system can be composed of chips, or can include chips and other discrete devices.

[0281] Figure 16 shows a structural diagram of a communication device 160, which is applied to the first node. Each module in the device shown in Figure 16 has the function of implementing the execution steps of the first node in Figures 8 to 14, and can achieve its corresponding technical effects. The corresponding beneficial effects of the execution steps of each module can be referred to the description of the corresponding steps in Figures 8 to 14, and will not be repeated here. The functions can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, the communication device includes:

[0282] The transceiver module 1601 is used to send first information to the second node, and the first information is used to query the processing capability and / or energy supply information of at least one third node; the transceiver module 1601 is also used to receive second information, and the second information indicates the processing capability and / or energy supply information of at least one third node; the processing module 1602 is used to determine at least one target third node for performing the task based on the second information.

[0283] Figure 17 shows a structural diagram of a communication device 170, which is applied to the second node. Each module in the device shown in Figure 17 has the function of implementing the execution steps of the second node in Figures 8 to 14, and can achieve its corresponding technical effects. The corresponding beneficial effects of the execution steps of each module can be referred to the description of the corresponding steps in Figures 8 to 14, and will not be repeated here. The functions can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, the communication device includes:

[0284] The transceiver module 1701 is used to receive first information, and the first information is used to query the processing capability and / or energy supply information of at least one third node; the processing module 1702 is used to determine second information based on the first information, and the second information indicates the processing capability and / or energy supply information of at least one third node; the transceiver module 1701 is also used to send the second information.

[0285] Figure 18 shows a structural diagram of a communication device 180, which is applied to the second node. Each module in the device shown in Figure 18 has the function of implementing the execution steps of the second node in Figures 8 to 14, and can achieve its corresponding technical effects. The corresponding beneficial effects of the execution steps of each module can be referred to the description of the corresponding steps in Figures 8 to 14, and will not be repeated here. The functions can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, the communication device includes:

[0286] The transceiver module 1801 is used to receive the fourth information, wherein the fourth information indicates a third node that needs to obtain the execution result of the task; the transceiver module 1801 is also used to receive the task parameters required for executing the task; the processing module 1802 is used to execute the task according to the task parameters and obtain the execution result of the task; the transceiver module 1801 is also used to send the execution result to the third node that needs to obtain the execution result of the task.

[0287] The embodiment of the present application further provides a communication system, comprising a first node and a second node, wherein the first node may have the function of the communication device 160 described above, and the second node may have the function of the communication device 170 described above.

[0288] In one embodiment, the communication system may further include a third node, and the third node may have the functionality of the communication device 180 described above.

[0289] The embodiments of the present application also provide a computer-readable storage medium. All or part of the processes in the above-mentioned method embodiments can be completed by a computer program to instruct the relevant hardware, and the program can be stored in the above-mentioned computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The computer-readable storage medium can be a terminal device of any of the above-mentioned embodiments, such as: an internal storage unit including a data sending end and / or a data receiving end, such as a hard disk or memory of the terminal device. The above-mentioned computer-readable storage medium can also be an external storage device of the above-mentioned terminal device, such as a plug-in hard disk, a smart memory card (smart media card, SMC), a secure digital (secure digital, SD) card, a flash card (flash card), etc. equipped on the above-mentioned terminal device. Furthermore, the above-mentioned computer-readable storage medium can also include both the internal storage unit of the above-mentioned terminal device and an external storage device. The above-mentioned computer-readable storage medium is used to store the above-mentioned computer program and other programs and data required by the above-mentioned terminal device. The above-mentioned computer-readable storage medium can also be used to temporarily store data that has been output or is to be output.

[0290] The present application also provides a computer instruction. All or part of the process in the above method embodiment can be completed by the computer instruction to instruct the relevant hardware (such as a computer, processor, network device, and terminal, etc.). The program can be stored in the above computer-readable storage medium.

[0291] The present application also provides a chip system. The chip system can be composed of a chip, or can include a chip and other discrete devices, without limitation. The chip system includes a processor and a transceiver. All or part of the process in the above method embodiment can be completed by the chip system. For example, the chip system can be used to implement the function performed by the first node in the above method embodiment, or to implement the function performed by the second node in the above method embodiment.

[0292] In one possible design, the above-mentioned chip system also includes a memory, which is used to store program instructions and / or data. When the chip system is running, the processor executes the program instructions stored in the memory to enable the chip system to perform the functions performed by the first node in the above-mentioned method embodiment or the functions performed by the second node in the above-mentioned method embodiment.

[0293] In the embodiments of the present application, the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0294] In an embodiment of the present application, the memory may be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), or a volatile memory (volatile memory), such as a random-access memory (RAM). The memory is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in an embodiment of the present application may also be a circuit or any other device that can implement a storage function, for storing instructions and / or data.

[0295] It should be noted that the terms "first" and "second" in the specification, claims, and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products, or devices.

[0296] It should be understood that in the embodiments of the present application, "at least one (item)" refers to one or more, "more than one" refers to two or more, "at least two (items)" refers to two or three and more than three, and "and / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple. It should be understood that in the embodiments of the present application, "B corresponding to A" means that B is associated with A. For example, B can be determined based on A. It should also be understood that determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information. In addition, the "connection" in the embodiments of the present application refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices, and the embodiments of the present application do not impose any limitation on this.

[0297] Unless otherwise specified, the "transmission" (transmit / transmission) appearing in the embodiments of the present application refers to bidirectional transmission, including the actions of sending and / or receiving. Specifically, the "transmission" in the embodiments of the present application includes the sending of data, the receiving of data, or the sending of data and the receiving of data. In other words, the data transmission here includes uplink and / or downlink data transmission. Data may include channels and / or signals, uplink data transmission is uplink channel and / or uplink signal transmission, and downlink data transmission is downlink channel and / or downlink signal transmission. The "network" and "system" appearing in the embodiments of the present application express the same concept, and the communication system is the communication network.

[0298] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0299] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0300] The units described as separate components may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0301] In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into a unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a device, such as a single-chip microcomputer, a chip, etc., or a processor to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, ROM, RAM, a magnetic disk or an optical disk. The above is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in the present application should be covered within the scope of protection of the present application. Therefore, the protection scope of this application should be based on the protection scope of the claims.

Claims

1. A communication method, characterized in that: Applied to the first node, including: Sending first information to the second node, where the first information is used to query processing capability and / or energy supply information of at least one third node; receiving second information indicating processing capability and / or power supply information of the at least one third node; At least one target third node for executing the task is determined according to the second information.

2. The communication method according to claim 1, characterized in that: The method further comprises: Sending third information to the second node, wherein the third information is used to indicate a third node that needs to obtain the execution result of the task and the at least one target third node.

3. The communication method according to claim 1 or 2, characterized in that: The second information includes identification information of the at least one third node and corresponding energy supply information; the method further includes: The time for each of the target third nodes to execute the task is determined according to the energy supply information in the second information.

4. The communication method according to any one of claims 1 to 3, characterized in that: The first information is also used to indicate the range information of the third node that needs to be queried.

5. The communication method according to any one of claims 1 to 4, characterized in that: The method further comprises: Sending sixth information to the second node, wherein the sixth information indicates a historical processing result of calling the task.

6. The communication method according to any one of claims 1 to 5, characterized in that: The task includes at least one of the following: model training, model testing, model simulation, model loading or model reasoning.

7. The communication method according to any one of claims 1 to 6, characterized in that: The processing capability includes at least one of the following: Hardware processing power, storage capacity, or hardware energy efficiency information; The energy supply information includes at least one of the following: The type of energy used to supply it, the time that energy is available, or the amount of carbon emissions per unit of energy.

8. A communication method, characterized in that: Applied to the second node, including: receiving first information, wherein the first information is used to query processing capability and / or energy supply information of at least one third node; Determine second information according to the first information, where the second information indicates processing capability and / or energy supply information of the at least one third node; The second information is sent.

9. The communication method according to claim 8, characterized in that: The method further comprises: receiving third information, where the third information is used to indicate a third node that needs to obtain the execution result of the task and a target third node for executing the task; Sending fourth information to a target third node that executes the task, wherein the fourth information indicates a third node that needs to obtain an execution result of the task.

10. The communication method according to claim 9, characterized in that: The method further comprises: receiving sixth information, wherein the sixth information indicates a call history processing result; The sixth information is sent to the target third node.

11. The communication method according to any one of claims 8 to 10, characterized in that: The first information is also used to indicate the range information of the third node that needs to be queried.

12. The communication method according to any one of claims 8 to 11, characterized in that: The method further comprises: Acquire processing capability and / or energy supply information of the at least one third node.

13. A communication method, characterized in that: The third node used to perform tasks includes: receiving fourth information, wherein the fourth information indicates a third node that needs to obtain the execution result of the task; Receive task parameters required to execute the task; Execute the task according to the task parameters to obtain an execution result of the task; The execution result is sent to a third node that requires the task.

14. The communication method according to claim 13, characterized in that: The third node for executing the task stores historical task parameters and corresponding historical processing results; Executing the task according to the task parameters to obtain the execution result of the task includes: The target historical processing result is determined as the execution result of the task, wherein the historical task parameter corresponding to the target historical processing result matches the task parameter.

15. A communication device, characterized in that: Applied to the first node, including: A transceiver module, configured to send first information to the second node, wherein the first information is used to query the processing capability and / or energy supply information of at least one third node; The transceiver module is further configured to receive second information, where the second information indicates the processing capability and / or energy supply information of the at least one third node; A processing module is used to determine at least one target third node for executing the task according to the second information.

16. The communication device according to claim 15, characterized in that: The device also includes: The transceiver module is used to send third information to the second node, wherein the third information is used to indicate the third node that needs to obtain the execution result of the task and the at least one target third node.

17. The communication device according to claim 15 or 16, characterized in that: The second information includes identification information of the at least one third node and corresponding energy supply information; the processing module is further used for: The time for each of the target third nodes to execute the task is determined according to the energy supply information in the second information.

18. The communication device according to any one of claims 15 to 17, characterized in that: The first information is also used to indicate the range information of the third node that needs to be queried.

19. The communication device according to any one of claims 15 to 18, characterized in that: The transceiver module is also used for: Sending sixth information to the second node, wherein the sixth information indicates a historical processing result of calling the task.

20. The communication device according to any one of claims 15 to 19, characterized in that: The task includes at least one of the following: model training, model testing, model simulation, model loading or model reasoning.

21. The communication device according to any one of claims 15 to 20, characterized in that: The processing capability includes at least one of the following: Hardware processing power, storage capacity, or hardware energy efficiency information; The energy supply information includes at least one of the following: The type of energy used to supply it, the time that energy is available, or the amount of carbon emissions per unit of energy.

22. A communication device, characterized in that: Applied to the second node, including: A transceiver module, configured to receive first information, wherein the first information is used to query processing capability and / or energy supply information of at least one third node; a processing module, configured to determine second information according to the first information, wherein the second information indicates a processing capability and / or energy supply information of the at least one third node; The transceiver module is further used to send the second information.

23. The communication device according to claim 22, characterized in that: The transceiver module is further used to receive third information, where the third information is used to indicate a third node that needs to obtain the execution result of the task and a target third node for executing the task; The transceiver module is further used to send fourth information to a target third node that executes the task, wherein the fourth information indicates the third node that requires the task.

24. The communication device according to claim 23, characterized in that The transceiver module is also used for: receiving sixth information, wherein the sixth information indicates a call history processing result; The sixth information is sent to the target third node.

25. The communication device according to any one of claims 22 to 24, characterized in that: The first information is also used to indicate the range information of the third node that needs to be queried.

26. The communication device according to any one of claims 22 to 25, characterized in that: The processing module is also used for: The processing capability and / or energy supply information of the at least one third node is obtained through the transceiver module.

27. A communication device, characterized in that: The third node used to perform tasks includes: A transceiver module, configured to receive fourth information, wherein the fourth information indicates a third node requiring the task; The transceiver module is also used to receive task parameters required for executing the task; A processing module, used for executing the task according to the task parameters and obtaining the execution result of the task; The transceiver module is also used to send the execution result to the third node that requires the task.

28. A communication device, characterized in that: The communication device comprises a processor and a transceiver, and the processor and the transceiver are used to support the communication device to execute the method according to any one of claims 1-14.

29. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed, the method according to any one of claims 1 to 14 is executed.

30. A communication system, characterized in that: The communication system includes a first node and a second node, or the communication system includes a first node, a second node and a third node, wherein the first node is used to execute the method as described in any one of claims 1-7, the second node is used to execute the method as described in any one of claims 8-12, and the third node is used to execute the method as described in claim 13 or 14.

Images