Resource management method, communication device, and storage medium

Abstract

The present disclosure provides a resource management method, a device, and a storage medium. The method is executed by a first device having a virtual digital twin (VDT) management capability. The method comprises: determining a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determining an agent on the first data twin resource pool; and executing, by the agent, the first service task, and determining, from the first data twin resource pool, a resource allocated for the first service task. Resources corresponding to service tasks can be adaptively determined to complete the service tasks, thereby improving resource utilization.

Description

A resource management method, communication device and storage medium Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a resource management method, communication device and storage medium. Background Technology

[0002] Due to the complexity of application scenarios, 6G services have rapidly changing demands for digital twin resources. The high dynamism and massive volume of demands for digital twin resources pose challenges to the optimization of service quality management of digital twin resources.

[0003] Summary of the Invention

[0004] This disclosure proposes a resource management method, communication equipment, communication system, and storage medium.

[0005] According to a first aspect of the present disclosure, a resource management method is proposed, executed by a first device, the first device having virtual digital twin (VDT) management capabilities. The method includes: determining a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determining an agent on the first data twin resource pool; having the agent execute the first service task, and determining resources allocated for the first service task from the first data twin resource pool.

[0006] In the above method, the resources allocated to the first service task can be determined and the first service task can be executed. This enables adaptive determination of the resources required for different tasks and intelligent optimization of the service quality of resource management.

[0007] According to a second aspect of the present disclosure, a first device is provided, including a processing module configured to: determine a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determine an agent on the first data twin resource pool; have the agent execute the first service task, and determine resources allocated for the first service task from the first data twin resource pool.

[0008] According to a third aspect of the present disclosure, a communication device is provided, comprising: one or more processors; wherein the one or more processors are configured to invoke instructions to cause the communication device to perform the methods described in any of the first aspects of the present disclosure.

[0009] According to a fourth aspect of the present disclosure, a storage medium is provided that stores instructions which, when executed on a communication device, cause the communication device to perform a method as described in any of the first aspects. Attached Figure Description

[0010] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0011] Figures 1a-1c are schematic flowcharts of some resource management methods provided in the embodiments of this disclosure;

[0012] Figure 2 is a flowchart illustrating some other resource management methods provided in the embodiments of this disclosure;

[0013] Figure 3 is a schematic diagram of a DTN network architecture provided in an embodiment of this disclosure;

[0014] Figure 4 is a schematic diagram of the structure of a Markov decision process model provided in an embodiment of this disclosure;

[0015] Figure 5 is a schematic diagram of the structure of a first device provided in an embodiment of this disclosure;

[0016] Figure 6a is a schematic diagram of the structure of a communication device provided in an embodiment of this disclosure;

[0017] Figure 6b is a schematic diagram of the structure of a chip provided in an embodiment of this disclosure. Detailed Implementation

[0018] This disclosure provides a resource management method, communication device, communication system, and storage medium.

[0019] In a first aspect, embodiments of this disclosure propose a resource management method, which is executed by a first device having virtual digital twin (VDT) management capabilities. The method includes: determining a first data twin resource pool corresponding to a first service request, wherein the first service request corresponds to a first service task; determining an agent on the first data twin resource pool; having the agent execute the first service task, and determining resources allocated for the first service task from the first data twin resource pool.

[0020] In the above embodiments, the resources allocated to the first service task can be determined and the first service task can be executed. This can achieve adaptive determination of the resources required for different tasks and intelligent optimization of the service quality of resource management.

[0021] In conjunction with some embodiments of the first aspect, in some embodiments, determining the first data twin resource pool corresponding to the first service request includes: decoupling the hardware resources of the physical network environment and the twin resources of the digital twin network (DTN) from the network device twin; placing the resources with the closest similarity scores into the same digital twin resource pool through data identification and model structure analysis to obtain multiple digital twin resource pools; and determining the first digital twin resource pool according to the resource requirement type of the first service request.

[0022] In the above embodiments, a first digital twin resource pool can be determined, which facilitates the determination of resources allocated to the first service task.

[0023] In conjunction with some embodiments of the first aspect, in some embodiments, determining the proxy on the first data twin resource pool includes: determining whether to accept the first service request based on the service demand of the first service task and the remaining resources in the first digital twin resource pool; and if the first service request is accepted, determining the proxy on the first data twin resource pool.

[0024] In the above embodiments, a proxy on the first data twin resource pool can be determined to facilitate the execution of the first service task.

[0025] In conjunction with some embodiments of the first aspect, in some embodiments, the agent performs the first service task and determines the resources allocated to the first service task from the first data twin resource pool, including: using a neural network model to determine action information at the first moment based on the DTN state information at the first moment, the action information being used to represent the resource allocation of the first service task; when the action information does not meet preset conditions, legalizing the action information through modulo operation to make the action information meet the preset conditions; and determining the resources allocated to the first service task from the first data twin resource pool based on the action information at the first moment and the response information corresponding to the action information.

[0026] In the above embodiments, the resources allocated to the first service task can be determined, and the resources allocated to different tasks can be adaptively determined to facilitate the execution of the first service task.

[0027] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: after the first service task is completed, obtaining the DTN network state at a second time point, wherein the second time point is a time point following the first time point.

[0028] In the above embodiments, the DTN network state at the second moment can be determined, which facilitates the determination of action information at the second moment.

[0029] In conjunction with some embodiments of the first aspect, in some embodiments, the DTN network state includes a vector of digital twin resource state and service requirements. The digital twin resource state includes at least one of the following: data twin DT location, used to indicate the edge server to which the data twin corresponding to the service task belongs; DT availability, used to indicate whether the service task is valid or invalid; and edge DT resource quantity, used to indicate the quantity of hardware resources and twin resources.

[0030] In the above embodiments, the DTN network status can be determined, which facilitates the determination of action information.

[0031] In conjunction with some embodiments of the first aspect, in some embodiments, the response information is a function of the service revenue and service cost of the first service task, and the response information includes at least one of the following: the difference between the service revenue and service cost of the first service task; the weighted sum of the service revenue and service cost of the first service task, wherein the service cost includes at least one of DT synchronization cost, DT orchestration cost, and server operation cost.

[0032] In the above embodiments, response information can be determined to facilitate the determination of resources allocated to the first service task.

[0033] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes at least one of the following: acquiring DTN status information and response information in real time from the digital twin network (DTN); acquiring historical DTN status information and historical response information from the edge server performing the first service task.

[0034] In the above embodiments, DTN status information and response information can be obtained, which facilitates the determination of resources allocated to the first service task.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes at least one of the following: registering a VDT for a first service request; periodically collecting service information and resource information of the service information; cleaning up the VDT after all DTs managed by the VDT have been executed; determining the resource allocation of all DTs managed by the VDT; and determining the digital twin resource usage strategy for executing the first service request according to the business operation process.

[0036] In a second aspect, embodiments of this disclosure propose a first device, including a processing module, configured to: determine a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determine a proxy on the first data twin resource pool; have the proxy execute the first service task, and determine the resources allocated for the first service task from the first data twin resource pool.

[0037] Thirdly, embodiments of this disclosure provide a communication device, which includes one or more processors; wherein the one or more processors are configured to invoke instructions to cause the communication device to perform the method of any one of the first aspects.

[0038] Fourthly, embodiments of this disclosure provide a storage medium storing computer-executable instructions; after being executed by a processor, the computer-executable instructions are capable of performing the methods described in the first aspect and the optional implementations of the first aspect.

[0039] It is understood that the aforementioned terminals, network devices, communication devices, communication systems, and storage media are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0040] This disclosure provides communication methods, communication devices, communication systems, and storage media. In some embodiments, the terms "communication method" and "information processing method" can be used interchangeably, as can the terms "terminal," "network device," and "communication apparatus," and the terms "information processing system" and "communication system."

[0041] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0042] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0043] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0044] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0045] In the embodiments disclosed herein, "multiple" refers to two or more.

[0046] In some embodiments, the terms “at least one of”, “at least one of”, “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0047] The descriptions in this disclosure, such as "at least one of A, B, C..." or "A and / or B and / or C...", include the case where any one of A, B, C... exists alone, as well as the case where any combination of any of A, B, C... exists alone. Each case can exist alone. For example, "at least one of A, B, C" includes the cases of A alone, B alone, C alone, A and B combination, A and C combination, B and C combination, and A and B and C combination. For example, A and / or B includes the cases of A alone, B alone, and A and B combination.

[0048] In some embodiments, the notation "in one case A, in another case B" or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: A is executed regardless of B, i.e., A is executed in some embodiments; B is executed regardless of A, i.e., B is executed in some embodiments; A and B are selectively executed, i.e., A and B are selected for execution in some embodiments; A and B are both executed, i.e., A and B are executed in some embodiments. The same applies when there are more branches such as A, B, and C.

[0049] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0050] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0051] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0052] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0053] In some embodiments, devices, etc., can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as “device”, “equipment”, “circuit”, “network element”, “node”, “function”, “unit”, “section”, “system”, “network”, “chip”, “chip system”, “entity”, and “subject” can be used interchangeably.

[0054] In some embodiments, the terms "access network device (AN device)," "radio access network device (RAN device)," "base station (BS)," "radio base station," "fixed station," "node," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "antenna panel," "antenna array," "cell," "macro cell," "small cell," "femto cell," "pico cell," "sector," "cell group," "carrier," "component carrier," and "bandwidth part (BWP)" can be used interchangeably.

[0055] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0056] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures that replace communication between access network devices, core network devices, or network devices and terminals with communication between multiple terminals (e.g., also referred to as device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, uplink link, downlink link, etc., can be replaced with sidelink link.

[0057] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0058] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0059] In some embodiments, the terms "uplink", "uplink", and "physical uplink" can be used interchangeably, as can the terms "downlink", "downlink", and "physical downlink", as well as the terms "sidelink", "sidelink", "sidelink communication", "sidelink communication", "direct connection", "direct link", "direct communication", and "direct link communication".

[0060] In some embodiments, the terms “downlink control information (DCI),” “downlink (DL) assignment,” “DL DCI,” “uplink (UL) grant,” and “UL DCI” can be used interchangeably.

[0061] In some embodiments, terms such as "physical downlink shared channel (PDSCH)" and "DL data" can be used interchangeably, as can terms such as "physical uplink shared channel (PUSCH)" and "UL data".

[0062] In some embodiments, the terms “radio”, “wireless”, “radio access network (RAN)”, “access network (AN)”, and “RAN-based” can be used interchangeably.

[0063] In some embodiments, the terms "synchronization signal (SS)," "synchronization signal block (SSB)," "reference signal (RS)," "pilot," and "pilot signal" can be used interchangeably.

[0064] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0065] In some embodiments, “get,” “obtain,” “get,” “receive,” “transmit,” “bidirectional transmission,” and “send and / or receive” can be used interchangeably and can be interpreted as receiving from other entities, obtaining from protocols, processing and obtaining on their own, or autonomously implementing, among other meanings.

[0066] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transfer,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0067] In some embodiments, "pre-defined" or "pre-set" can be interpreted as pre-specified in an agreement or the like, or as a device or the like performing a pre-set action.

[0068] In some embodiments, determining can be interpreted as judging, deciding, judging, calculating, computing, processing, deriving, investigating, searching, looking up, searching, querying, ascertaining, receiving, transmitting, inputting, outputting, accessing, resolving, selecting, choosing, establishing, comparing, assuming, expecting, considering, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc., but is not limited to these.

[0069] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (boolean), or by a comparison of numerical values ​​(e.g., a comparison with a predetermined value), but is not limited thereto.

[0070] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0071] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data after receiving it; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0072] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0073] In some embodiments, data, information, etc., may be obtained after obtaining user consent. To address the above-mentioned problems, this disclosure proposes an information indication method, a communication device, a communication system, and a storage medium.

[0074] In some embodiments, this disclosure can be applied to a communication system, wherein the communication system may include a first device, which may be an edge server; or the communication system may include a first device and at least one edge server; or the communication system may include at least one edge server, wherein the edge server has the functions of the first device, or may act as the first device.

[0075] The number and form of the entities included in the above communication system are arbitrary, and the connection relationship between the entities is illustrative. The entities may or may not be connected to each other, and the connection can be in any way, such as direct connection or indirect connection, wired connection or wireless connection.

[0076] In some embodiments, the first device may be used to provide services to a terminal, which includes, but is not limited to, at least one of the following: a mobile phone, a wearable device, an Internet of Things device, a car with communication capabilities, a smart car, a tablet computer, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and a wireless terminal device in a smart home.

[0077] In some embodiments, the access network device is, for example, a node or device that connects a terminal to a wireless network. The access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation eNB (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in 6th generation mobile networks (6G), open RAN, cloud RAN, base station in other communication systems, and access node in a wireless fidelity (WiFi) system.

[0078] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0079] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some of the protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0080] In some embodiments, a core network device may be a single device comprising one or more network elements, or it may be multiple devices or a group of devices, each comprising all or part of one or more network elements. Network elements may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), or a Next Generation Core (NGC).

[0081] In some embodiments, the above-mentioned one or more network elements may include, for example, AMF, UPF, MME, etc., and may also include other network elements, such as Policy Control Function (PCF), Application Function (AF), Network Application Function (NAF), Authentication and Key Management for Applications Anchor Function (AAnF), Bootstrapping Server Functionality (BSF), Session Management Function (SMF), etc.

[0082] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0083] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, Ultra-Wideband (UWB), Bluetooth (a registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them, etc. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0084] A digital twin is a virtual model designed to accurately reflect a physical object. It equips the object with various sensors related to key functional aspects. These sensors generate data related to various aspects of the physical object's performance, such as energy output, temperature, and weather conditions. This data is then forwarded to a processing system and applied to the digital copy.

[0085] Once such data is obtained, the virtual model can be used to run simulations, study performance issues, and generate possible improvements; all of this is to gain valuable insights that can then be applied to the original physical objects.

[0086] Although both simulation and digital twins use digital models to replicate various processes of a system, a digital twin is actually a virtual environment, offering particularly rich content for research. The main difference between digital twins and simulations lies in scale: simulations typically study a specific process, while digital twins can run any number of practical simulation projects to study multiple processes.

[0087] Of course, the differences between the two go far beyond that. For example, simulations typically don't benefit from acquiring real-time data. But digital twins are designed around a two-way flow of information. This flow first occurs when the object's sensors provide relevant data to the system's processor. Then, it occurs again when the processor shares its insights with the original source object.

[0088] Digital twins possess higher quality and more constantly updated data, covering a wider range of fields. In addition, the virtual environment has stronger computing power. Therefore, compared with standard simulations, digital twins can study more issues from a more advantageous perspective and have greater ultimate potential to improve products and processes.

[0089] The rapidly growing demand for services from emerging 6G mobile networks, coupled with the dynamic changes in the demand for digital twin resources, presents challenges to the optimization of Service Quality (QoS) management for digital twin resources.

[0090] Emerging 6G services, due to their complex application scenarios, have rapidly changing demands for digital twin resources. Current digital twin resource management technologies have overlooked the highly dynamic and massive requirements of 6G services. Adaptive configuration and intelligent orchestration of DTN resources for large-scale 6G service responses remain unresolved issues.

[0091] To address the aforementioned issues, this disclosure proposes a resource management method that can adapt to the diverse needs of 6G services. This architecture integrates DTN with edge virtualization to adaptively respond to 6G service demands. The specific details of this method are shown below.

[0092] Figure 1a is a flowchart illustrating a resource management method according to an embodiment of the present disclosure. As shown in Figure 1a, this embodiment of the present disclosure relates to a resource management method for a first device 101, the method comprising:

[0093] Step 1101: Register VDT.

[0094] In some embodiments, the first device can register a VDT for a first service request. The first device may include a VDT manager. The registration component of the VDT manager can register a VDT for the first service request after receiving it, so as to facilitate the management of the first service request. In other words, after the first service request is registered to a VDT, the first service request can be managed by that VDT.

[0095] In some embodiments, for example, a first service request may be used to request relevant resources to perform a first service task, which may be a digital twin virtualization service, etc. For example, the first service task may construct a virtual digital twin, i.e., a VDT, by scheduling digital virtual twin resources.

[0096] Step 1102: Collect service information and resource information related to the service information.

[0097] In some embodiments, the first device may periodically collect service information and resource information related to the service information. For example, the first device may periodically collect service information through the monitor of the VDT manager. For example, the service information may be information about a first service request, and the resource information of the service information may be resource information required by the service during execution.

[0098] Step 1103: Determine the first data twin resource pool.

[0099] In some embodiments, the first device may determine the first data twin resource pool corresponding to the first service request, wherein the first service request corresponds to the first service task, that is, the first service request can be used to request resources to execute the first service task.

[0100] In some embodiments, determining the first data twin resource pool corresponding to the first service request includes:

[0101] Decouple the hardware resources of the physical network environment from the twin resources of the digital twin network (DTN) from the network device twin;

[0102] By identifying data and analyzing model structures, resources with the closest similarity scores are placed into the same digital twin resource pool, resulting in multiple digital twin resource pools.

[0103] The first digital twin resource pool is determined based on the resource requirement type of the first service request.

[0104] For example, hardware resources may include computing resources, storage resources, etc., while twin resources may include dataset resources, model resources, etc.

[0105] In some embodiments, the first data twin resource pool may include the resources required by the first service task.

[0106] Step 1104: Determine the agent on the first data twin resource pool.

[0107] In some embodiments, determining the agent on the first data twin resource pool includes:

[0108] Based on the business demand of the first service task and the remaining resources in the first digital twin resource pool, determine whether to accept the first service request; if the first service request is accepted, determine the proxy on the first data twin resource pool.

[0109] In other words, the resource requirements of the first service task can be determined, such as the types of resources required by the first service task and the quantity of each type of resource. By determining the relationship between the remaining resources in the first digital twin resource pool and the required amount, it can be determined whether to accept the first service request. For example, if the remaining resources in the first digital twin resource pool can meet the requirements of the first service task, the first service request can be accepted; or, if the resources required by the first service task are lacking in the first digital twin resource pool, the first service request can be rejected.

[0110] In some embodiments, the agent on the first data twin resource pool can perform business process operations on the first service request, that is, the agent can perform the operation of the first service task.

[0111] Step 1105: Determine the resource allocation for all DTs managed by the VDT.

[0112] In some embodiments, a VDT can manage one or more DTs, and the first device can determine the resource allocation of all DTs managed by the VDT.

[0113] In some embodiments, a service task can generate a DT, that is, the VDT manager of the first device can manage multiple digital twin service tasks. The VDT manager can allocate resources according to the resources required by the DT (i.e. the resources required by the service task corresponding to the DT) and the resources in the data twin resource pool managed by the VDT, and allocate corresponding resources to each DT managed by the VDT to complete the service task corresponding to the DT.

[0114] In some embodiments, for example, after allocating resources to all DTs managed by the VDT, a response can be generated to indicate the resource allocation result. For example, the first device can refer to the response to allocate resources for the first service task.

[0115] In some embodiments, when a VDT manages multiple DTs, resources can be allocated reasonably to multiple first service tasks by allocating resources to all DTs managed by the VDT.

[0116] Step 1106: Determine the digital twin resource usage strategy for executing the first service request.

[0117] In some embodiments, the first device may determine the digital twin resource usage strategy for executing the first service request based on the business operation process.

[0118] In some embodiments, the digital twin resource usage policy of the first service request may be action information. The digital twin resource usage policy of the first service request may be used to indicate which resources are allocated to perform the first service task. The first device may determine the resources allocated to the first service task based on the digital twin resource usage policy of the first service request.

[0119] Step 1107: Determine the resources allocated for the first service task from the first data twin resource pool.

[0120] In some embodiments, the first device may use a neural network model to determine action information at a first moment based on the DTN state information at a first moment, and the action information is used to represent the resource allocation of the first service task.

[0121] In some embodiments, for example, the first moment can be the current moment. For example, the first device can obtain DTN status information and response information in real time from the digital twin network (DTN); or the first device can obtain historical DTN status information and historical response information from the edge server performing the first service task.

[0122] Optionally, when the first device can obtain DTN status information and response information from the digital twin network (DTN) in real time, it can update the action information at the first moment online. In this case, the DTN status information and response information obtained by the first device can be the DTN status information and response information determined at the previous moment.

[0123] Optionally, when the first device can obtain historical DTN status information and historical response information from the edge server executing the first service task, it can update the action information at the first moment offline. For example, the edge server executing the first service task can store some historical DTN status information and historical response information. In other words, the DTN status information and response information determined within a certain period of time can be stored on the edge server executing the first service task. The edge server executing the first service task can determine the action information at the first moment based on the stored historical data.

[0124] In some embodiments, optionally, multiple action information can be determined for the first service task. For example, the initial action information can be a preset value, or action information determined based on historical data, or initial action information determined according to the parameters of the neural network. In this case, the initial action information may not meet the requirements of the first service task. Then, the action information at the first moment can be determined according to the DTN state at the first moment to update the action information. For example, the action information can be updated cyclically until the action information meets the requirements of the first service task or meets other set conditions. This disclosure does not limit this.

[0125] In some embodiments, when updating action information, a neural network model can be used. Optionally, the neural network model may include an evaluation network for evaluating the updated action information. For example, the action information can be evaluated using a loss function. The evaluation can yield a response reward, which can be used to evaluate the current action information. For example, points are added when the current action information is good and points are deducted when the current action information is poor. For example, good action information may indicate that the resource allocation scheme indicated by the action information has high resource utilization and low resource waste. When the value of the loss function is less than a threshold, it can be determined that the current action information meets the requirements.

[0126] In the above embodiments, optionally, the loss function can be a function of the difference between the target neural network model and the current neural network model.

[0127] In some embodiments, action information may be used to indicate the resources allocated to the first service task, such as the type and quantity of resources allocated to the first service task.

[0128] In some embodiments, the action information at the first moment can be determined based on the state information of the DTN at the first moment, and the response information corresponding to the action information can be obtained. For example, the parameters of the neural network model can be adjusted based on the response information to optimize the model, and the action information can be updated based on the optimized model.

[0129] For example, the response information can be a numerical value, namely the reward value. This value can be set according to the actual use case. For example, when the action information output by the current model meets expectations, the corresponding reward value can be set to a positive value; when the action information output by the current model does not meet expectations, the corresponding reward value can be set to a negative value. In particular, the reward value can be set to 0 in some scenarios. For example, when determining the action information of a service task again after it has been virtualized, the value corresponding to the obtained action information can be set to 0, or when the current model does not need to be adjusted, the value corresponding to the obtained action information can be set to 0. Alternatively, other reward values ​​can be set as needed, which is not limited in this disclosure.

[0130] In some embodiments, when the action information does not meet the preset conditions, the first device can legalize the action information through modulo operation so that the action information meets the preset conditions.

[0131] In the above embodiments, the preset condition can also be that the first service task has been completed. Since the service task has been virtualized, the action information determined after the completion of the execution is invalid action information. At this time, the action information can be legalized by modulo operation. For example, action information that does not meet the preset condition can be removed.

[0132] In the above embodiments, the preset condition can also be that the action information is within a reasonable resource range. In other words, a reasonable resource range can be allocated for the first service task. When the action information does not meet the preset condition, that is, the resources allocated to the first service task indicated by the action information are within an unreasonable resource range, the action information can be legalized by modulo operation. For example, the action information that does not meet the preset condition can be removed.

[0133] In some embodiments, the first device may determine the resources allocated for the first service task from the first data twin resource pool based on the action information at a first moment and the response information corresponding to the action information.

[0134] In some embodiments, the response information is a function of the service revenue and service cost of the first service task, and the response information includes at least one of the following:

[0135] The difference between the service revenue and service cost of the first service task;

[0136] The first service task is a weighted sum of service revenue and service costs, where the service costs include at least one of DT synchronization costs, DT orchestration costs, and server operation costs.

[0137] In some embodiments, the first device may determine action information based on response information, and determine the resources allocated for the first service task from the first data twin resource pool according to the content indicated by the action information, for completing the first service task.

[0138] Step 1108: The agent performs the first service task.

[0139] In some embodiments, the agent may use the resources allocated to the first service task to complete the first service task.

[0140] Step 1109: Obtain the DTN network state at the second time step.

[0141] In some embodiments, the first device may obtain the DTN network status at a second time after the first service task is completed, wherein the second time is a time after the first time.

[0142] In other words, the first device can update the DTN network status after the first service task is completed.

[0143] In some embodiments, the DTN network state includes a vector of digital twin resource states and service requirements, wherein the digital twin resource states include at least one of the following:

[0144] The data twin DT location is used to indicate the edge server to which the data twin corresponding to the service task belongs;

[0145] DT availability is used to indicate whether a service task is valid or invalid.

[0146] Edge DT resource quantity is used to represent the quantity of hardware resources and twin resources.

[0147] In some embodiments, DT availability can be used to indicate the current state of a DT. For example, when the service task corresponding to a DT has been completed or canceled, the service task corresponding to the DT is invalid and the DT is unavailable.

[0148] Step 1110: Clean up the VDT.

[0149] In some embodiments, after all the DTs managed by a VDT have been executed, the VDT can be cleaned up. In other words, when all the service tasks corresponding to all the DTs managed by a VDT have been completed, the VDT expires and can be cleaned up.

[0150] In some embodiments, this step is optional, and it is not necessary to clean up the VDT if not all DTs managed by the VDT have been executed.

[0151] The method involved in the embodiments of this disclosure may include at least one of steps 1101 to 1110. For example, steps 1101+1102+1103+1104+1105+1106+1107+1108+1109+1110 can be implemented as an independent embodiment, steps 1101+1102+1103+1104+1105+1106+1107+1108+1109 can be implemented as an independent embodiment, and steps 1101+1102+1103+1104+1105+110... Steps 6+1107+1108 can be implemented as independent embodiments, and steps 1101+1102+1103+1104+1105+1107+1108 can be implemented as independent embodiments, but are not limited thereto.

[0152] Figure 1b is a flowchart illustrating a resource management method according to an embodiment of the present disclosure. As shown in Figure 1b, this embodiment of the present disclosure relates to a resource management method for a first device 101, the method comprising:

[0153] Step 1201: Register VDT.

[0154] The optional implementation of step 1201 can be found in the optional implementation of step 1101 in Figure 1a and other related parts in the embodiments involved in Figure 1a, which will not be repeated here.

[0155] Step 1202: Collect service information and resource information related to the service information.

[0156] The optional implementation of step 1202 can be found in the optional implementation of step 1102 in Figure 1a and other related parts in the embodiments involved in Figure 1a, which will not be repeated here.

[0157] Step 1203: Determine the first data twin resource pool.

[0158] The optional implementation of step 1203 can be found in the optional implementation of step 1103 in Figure 1a and other related parts in the embodiments involved in Figure 1a, which will not be repeated here.

[0159] Step 1204: Determine the agent on the first data twin resource pool.

[0160] The optional implementation of step 1204 can be found in the optional implementation of step 1104 in Figure 1a and other related parts in the embodiment involved in Figure 1a, which will not be repeated here.

[0161] Step 1205: Determine the resource allocation for all DTs managed by the VDT.

[0162] The optional implementation of step 1205 can be found in the optional implementation of step 1105 in Figure 1a and other related parts in the embodiment involved in Figure 1a, which will not be repeated here.

[0163] Step 1206: Determine the digital twin resource usage strategy for executing the first service request.

[0164] The optional implementation of step 1206 can be found in the optional implementation of step 1106 in Figure 1a and other related parts in the embodiment involved in Figure 1a, which will not be repeated here.

[0165] Step 1207: Determine the resources allocated for the first service task from the first data twin resource pool.

[0166] The optional implementation of step 1207 can be found in the optional implementation of step 1107 in Figure 1a and other related parts in the embodiments involved in Figure 1a, which will not be repeated here.

[0167] Step 1208: The agent performs the first service task.

[0168] The optional implementation of step 1208 can be found in the optional implementation of step 1108 in Figure 1a and other related parts in the embodiment involved in Figure 1a, which will not be repeated here.

[0169] Step 1209: Obtain the DTN network state at the second time step.

[0170] The optional implementation of step 1209 can be found in the optional implementation of step 1109 in Figure 1a and other related parts in the embodiments involved in Figure 1a, which will not be repeated here.

[0171] Figure 1c is a flowchart illustrating a resource management method according to an embodiment of the present disclosure. As shown in Figure 1c, this embodiment of the present disclosure relates to a resource management method for a first device 101, the method comprising:

[0172] Step 1301: Determine the first data twin resource pool.

[0173] Optional implementations of step 1301 can be found in step 1103 of Figure 1a, optional implementations of step 1203 of Figure 1b, and other related parts in the embodiments of Figures 1a and 1b, which will not be repeated here.

[0174] Step 1302: Determine the agent on the first data twin resource pool.

[0175] Optional implementations of step 1302 can be found in step 1104 of Figure 1a, optional implementations of step 1204 of Figure 1b, and other related parts in the embodiments of Figures 1a and 1b, which will not be repeated here.

[0176] Step 1303: Determine the resources allocated for the first service task from the first data twin resource pool.

[0177] Optional implementations of step 1303 can be found in step 1107 of Figure 1a, optional implementations of step 1207 of Figure 1b, and other related parts in the embodiments of Figures 1a and 1b, which will not be repeated here.

[0178] Step 1304: The agent performs the first service task.

[0179] Optional implementations of step 1304 can be found in step 1108 of Figure 1a, optional implementations of step 1208 of Figure 1b, and other related parts in the embodiments of Figures 1a and 1b, which will not be repeated here.

[0180] Figure 2 is an interactive schematic diagram illustrating a resource management method according to an embodiment of the present disclosure. As shown in Figure 2, the embodiments of the present disclosure relate to a resource management method, which includes:

[0181] Step 2101: The first device determines the first data twin resource pool.

[0182] The optional implementation of step 2101 can be found in the optional implementation of step 1103 in Figure 1a, step 1203 in Figure 1b, step 1301 in Figure 1c, and other related parts in the embodiments involved in Figures 1a, 1b, and 1c, which will not be repeated here.

[0183] Step 2102: The first device determines the agent on the first data twin resource pool.

[0184] Optional implementations of step 2102 can be found in step 1104 of Figure 1a, step 1204 of Figure 1b, step 1302 of Figure 1c, and other related parts in the embodiments of Figures 1a, 1b, and 1c, which will not be repeated here.

[0185] Step 2103: The first device determines the resources allocated for the first service task from the first data twin resource pool.

[0186] Optional implementations of step 2103 can be found in step 1107 of Figure 1a, step 1207 of Figure 1b, step 1303 of Figure 1c, and other related parts in the embodiments of Figures 1a, 1b, and 1c, which will not be repeated here.

[0187] Step 2104: The agent of the first device performs the first service task.

[0188] The optional implementation of step 2104 can be found in the optional implementation of step 1108 in Figure 1a, step 1208 in Figure 1b, step 1301 in Figure 1c, and other related parts in the embodiments involved in Figures 1a, 1b, and 1c, which will not be repeated here.

[0189] The following is an exemplary description of the above method.

[0190] The method illustrated in this disclosure relates to a 6G service response digital twin function virtualization method based on deep reinforcement learning.

[0191] This example reshapes the DTN architecture based on software-defined networking (SDN) technology to facilitate the management of digital twin networks (DTN).

[0192] The DTN architecture includes a digital twin network layer, as shown in Figure 3, which comprises a physical network domain and a twin network domain. In the physical network domain, 6G heterogeneous physical network devices (such as vehicles, drones, and robots) connect to twin models on mobile edge servers via real-time communication. The twin network domain consists of edge servers equipped with twin network devices. These edge servers exchange DT information via the OpenFlow interface, with flow tables indicating corresponding forwarding rules. The architecture also includes a digital twin function virtualization (DTFV) layer, which is the core of adaptive service response and intelligent digital twin resource orchestration. This solution sets up an SDN controller with online and AI-based digital twin resource orchestration strategies to optimize quality of service.

[0193] In some embodiments, the physical network domain can be an actual network, and the twin network domain can be obtained by virtualizing the physical network domain and can be used to simulate events in the physical network.

[0194] The workflow for digital twin function virtualization is as follows.

[0195] First, service requests can be received. These requests request resources to execute service tasks. Each service request corresponds to a Data Controller (DT), and DTs can be registered with Virtual Data Controllers (VDTs) for management. To manage VDTs in the DTFV (Digital Twin-Based Virtualization), a VDT manager is set up for registering, monitoring, orchestrating, and configuring VDTs. The VDT registration component is responsible for registering VDTs in the DTN (Digital Twin Network) for newly arriving service requests. To monitor the global state of VDTs and DTFV resources, a VDT monitor can be set up to periodically collect data such as service requests and resources, and to clean up expired VDTs. The VDT business process component can learn the optimal DTFV resource business process operations for each VDT and allocate resources to the DTs managed by the VDTs. The SDN (Digital Twin Network) can then determine the resources allocated to service tasks based on the resource allocation determined by the VDTs. The VDT configuration component can formulate digital twin resource usage strategies for edge servers based on dynamic business process operations.

[0196] For example, the VDT manager, like a basic digital twin with data acquisition, model updates, and physical control capabilities, can also implement these digital twin functions through virtualized resources. Taking a real-world 6G autonomous driving service as an example, DTFV first creates a VDT associated with multiple isomorphic vehicle twins, with the associated vehicle twins sharing hardware and twin resources. Based on this, because the number of virtualized vehicle twins can be flexibly adjusted, the twin data acquisition function of the VDT in the autonomous driving service is enhanced and extended. Furthermore, the model update function of the VDT is jointly implemented by these associated vehicle digital twins. Moreover, compared to a basic vehicle digital twin, the control object of the VDT in the autonomous driving service is a group of physical vehicles, and the commands fed back to each vehicle are customized.

[0197] Upon receiving a service request, the corresponding DT resource pool, i.e., the digital twin resource pool, can be determined. This resource pool can include resources available for the service task corresponding to the service request. Specifically, the method for determining the resource pool includes: In the proposed DTFV, hardware resources (e.g., computing resources, storage resources) and twin resources (e.g., dataset resources, model resources) are first decoupled from the network device twin. Through data identification and model structure analysis, resources with the closest similarity scores are placed in the same digital twin resource pool. When executing a service task, these virtual digital twin resources can be intelligently scheduled to achieve the service task, i.e., constructing a virtual digital twin (VDT).

[0198] After determining the digital twin resource pool, the VDT manager can allocate resources for the DTs managed by the VDT. The result of this allocation can be the response in Figure 3. As shown in Figure 3, after determining the response, the VDT manager can send the response to the SDN, facilitating the SDN to determine the resources ultimately allocated to the service task based on this response.

[0199] Based on the above response, the SDN can orchestrate resources according to the Deep Reinforcement Learning (DRL) strategy to obtain the resources allocated to the service task. The specific orchestration scheme is as follows.

[0200] There are two stages in the proposed DTFV resource orchestration scheme.

[0201] In the pre-orchestration stage, the digital twin resource pool is first determined by the service resource demand type.

[0202] Then, an initial business acceptance decision is made based on the business demand volume and the number of remaining available resources in the selected DT pool.

[0203] In the DRL-based business process stage, the agent on the selected DT pool performs business process operations on all accepted service requests according to the current policy. At the same time, the agent policy is updated regularly to facilitate online learning of dynamic business demands and DTN environment characteristics. In other words, the agent can be used to execute service tasks.

[0204] Assume that at time slot t (i.e., at time t) in the DTN environment, there are K pairs of digital twins D = {D1, D2,..., DK}, M edge servers that can be represented as G = {g1, g2,..., GM}, and N business requests V = {v1, v2,..., VN}. Each edge server can manage a random number of DTs. For each edge server Gi (0 < i ≤ M), it can process multiple DTs, which can be represented as (DGi, Bi), where Bi represents the number of DTs processed by this edge server.

[0205] To solve the DTFV resource orchestration problem, a Markov Decision Process (MDP) model is constructed as shown in Figure 4. This model consists of the DTN state S, the orchestration action A, and the response reward R.

[0206] The overall resource orchestration process can include obtaining an orchestration action A for the service task corresponding to the DT according to the DTN state S, and a response reward R for evaluating the orchestration action A, and adjusting the orchestration action A according to the response reward R to obtain the final resource orchestration action.

[0207] The state st∈S of the DTN can be defined as a vector containing the digital twin resource state Qt and service requirements, denoted by st=(Qt,Vt). The digital twin resource state Qt includes the DT location Li t∈{1,2,…,M}, the DT availability Fti∈{0,1}, and the edge DT resource quantity Dti.

[0208] Orchestration Actions also include defining the DTFV resource orchestration action space across all servers as a discrete vector containing a global DT index index k = 1, 2, ..., K. In other words, for each DT, an orchestration action can be obtained based on its DTN state. This orchestration action is the resource allocation orchestration action, used to indicate the resources allocated to that DT. Therefore, an index can be set for each DT or each resource orchestration action. An action represents the method of resource allocation for the current response service when a specific DT is virtualized. For time-critical service tasks, the business response process will not end until the virtualized DT meets all business requirements within the service time.

[0209] In the above embodiments, the response reward value can be set manually. To optimize global QoS, we define the reward as the profit of the service response, i.e., the difference between service revenue and service cost. Then, the reward R is defined as the weighted sum of service revenue and service cost. In particular, an additional zero value can be set to terminate the current service response. For example, after terminating the service response, when updating the action information again, the response reward value can be 0, indicating that there is no need to determine the action information again. After the number of times the response reward value is 0 reaches a threshold, updating the action information can be stopped.

[0210] The final action space obtained from the above business process operations can be represented as A = {0, 1, 2, 3, ..., K}. To prevent the agent from performing illegal actions in DTFV resource orchestration, such as selecting a virtualized DT, we further map these illegal actions to legal actions through modular arithmetic.

[0211] The resource orchestration process described above can be implemented using the Proximal Policy Optimization-Proximal Policy Optimization (PPO-DRL) resource orchestration algorithm.

[0212] To improve the data efficiency and robustness of the policy, this algorithm proposes a new objective function based on the Policy Gradient (PG) algorithm and near-end policy optimization, namely the PPO-DRL algorithm mentioned above, which can achieve mini-batch updates over multiple epochs.

[0213] In summary, the above embodiments of this solution propose a software-defined DTN architecture integrating Digital Twin Function Virtualization (DTFV). This architecture possesses service awareness capabilities and provides a flexible digital twin resource management method, capable of adapting to the diverse needs of 6G services. A DTFV resource orchestration algorithm based on PPO-DRL intelligently responds to massive edge services through global QoS optimization. A decoupled and shared DTFV method based on heterogeneous network device digital twins is proposed, reconstructing an enhanced and scalable dual-function DTN. Furthermore, a DRL-based digital twin resource orchestration algorithm adaptively responds to dynamic service requests, intelligently optimizing DTFV service quality.

[0214] Figure 5 is a schematic diagram of the structure of the first device 101 proposed in this embodiment. As shown in Figure 5, the first device 101 includes: a processing module 5101, configured to: determine a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determine a proxy on the first data twin resource pool; have the proxy execute the first service task, and determine the resources allocated for the first service task from the first data twin resource pool; optionally, the above processing module is configured to execute at least one of the sending and receiving related steps (e.g., steps 2101, 2102, 2103, 2104, 2105, 2106, 2107, 2108, 2109, 2110, etc., but not limited thereto) executed by the first device 101 in any of the above methods, which will not be described in detail here.

[0215] In some embodiments, the processing module 5101 can also be used to register a VDT.

[0216] In some embodiments, the processing module 5101 can also be used to collect service information and resource information related to the service information.

[0217] In some embodiments, the processing module 5101 can also be used to determine the resource allocation of all DTs managed by the VDT.

[0218] In some embodiments, the processing module 5101 may also be used to determine the digital twin resource usage strategy for executing the first service request.

[0219] In some embodiments, the processing module 5101 can also be used to obtain the DTN network status at a second time.

[0220] In some embodiments, the processing module 5101 can also be used to clean up the VDT.

[0221] As shown in Figure 6a, the communication device 6100 includes one or more processors 6101. The processor 6101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU). The baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. The processor 6101 is used to invoke instructions to cause the communication device 6100 to execute any of the above methods.

[0222] In some embodiments, the communication device 6100 further includes one or more memories 6102 for storing instructions. Optionally, all or part of the memories 6102 may also be located outside the communication device 6100.

[0223] In some embodiments, the communication device 6100 further includes one or more transceivers 6103. When the communication device 6100 includes one or more transceivers 6103, the communication steps such as sending and receiving in the above method are performed by the transceivers 6103, and other steps are performed by the processor 6101.

[0224] In some embodiments, a transceiver may include a receiver and a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, etc., may be used interchangeably; the terms transmitter, transmitting unit, transmitter, transmitting circuit, etc., may be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., may be used interchangeably.

[0225] Optionally, the communication device 6100 further includes one or more interface circuits 6104 connected to the memory 6102. The interface circuits 6104 can be used to receive signals from the memory 6102 or other devices, and can be used to send signals to the memory 6102 or other devices. For example, the interface circuits 6104 can read instructions stored in the memory 6102 and send the instructions to the processor 6101.

[0226] The communication device 6100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 6100 described in this disclosure is not limited thereto, and the structure of the communication device 6100 may not be limited by FIG. 6a. The communication device may be a standalone device or a part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0227] Figure 6b is a schematic diagram of the structure of chip 6200 according to an embodiment of this disclosure. For cases where the communication device 6100 can be a chip or a chip system, please refer to the schematic diagram of chip 6200 shown in Figure 6b, but it is not limited thereto.

[0228] Chip 6200 includes one or more processors 6201, which are used to invoke instructions to cause chip 6200 to perform any of the above methods.

[0229] In some embodiments, chip 6200 further includes one or more interface circuits 6202 connected to memory 6203. Interface circuits 6202 can be used to receive signals from memory 6203 or other devices, and can also be used to send signals to memory 6203 or other devices. For example, interface circuit 6202 can read instructions stored in memory 6203 and send those instructions to processor 6201. Optionally, terms such as interface circuit, interface, transceiver pin, and transceiver can be used interchangeably.

[0230] In some embodiments, chip 6200 further includes one or more memories 6203 for storing instructions. Optionally, all or part of the memories 6203 may be located outside of chip 6200.

[0231] This disclosure also proposes a storage medium storing instructions that, when executed on the communication device 6100, cause the communication device 6100 to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0232] This disclosure also provides a program product that, when executed by the communication device 6100, causes the communication device 6100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0233] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

[0234] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer programs. When the computer program is loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this disclosure are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer program can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program can be transferred from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0235] The correspondences shown in the tables of this disclosure can be configured or predefined. The values ​​of the information in each table are merely examples and can be configured to other values; this disclosure is not limiting. When configuring the correspondences between information and parameters, it is not necessarily required to configure all the correspondences shown in each table. For example, the correspondences shown in some rows of the tables in this disclosure may not be configured. Furthermore, appropriate modifications and adjustments can be made based on the above tables, such as splitting, merging, etc. The names of the parameters shown in the headers of the above tables can also use other names that the communication device can understand, and the values ​​or representations of the parameters can also be other values ​​or representations that the communication device can understand. In the implementation of the above tables, other data structures can also be used, such as arrays, queues, containers, stacks, linear lists, pointers, linked lists, trees, graphs, structures, classes, heaps, hash tables, or hash tables, etc.

[0236] The predefined terms in this disclosure can be understood as defined, predefined, stored, pre-stored, pre-negotiated, pre-configured, solidified, or pre-burned.

[0237] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0238] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0239] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A resource management method characterized by, The method is executed by a first device having virtual digital twin (VDT) management capability, and comprises: determining a first data twin resource pool corresponding to a first service request, the first service request corresponding to a first service task; determining an agent on the first data twin resource pool; executing the first service task by the agent and determining resources allocated to the first service task from the first data twin resource pool.

2. The method of claim 1, wherein, The determining of the first data twin resource pool corresponding to the first service request comprises: decoupling hardware resources of a physical network environment and twin resources of a digital twin network (DTN) from network device twins; putting resources with the closest similarity scores into the same digital twin resource pool through data recognition and model structure analysis to obtain a plurality of digital twin resource pools; determining the first digital twin resource pool according to a resource requirement type of the first service request.

3. The method according to claim 1 or 2, characterized in that, The determining of the agent on the first data twin resource pool comprises: determining whether to accept the first service request according to a service demand of the first service task and a remaining resource quantity in the first digital twin resource pool; in a case where the first service request is accepted, determining the agent on the first data twin resource pool.

4. The method according to any one of claims 1 to 3, characterized in that, The executing of the first service task by the agent and the determining of the resources allocated to the first service task from the first data twin resource pool comprise: using a neural network model to determine action information at a first time based on DTN state information at the first time, the action information being used to represent resource allocation of the first service task; in a case where the action information does not satisfy a preset condition, legalizing the action information through a modulo operation to make the action information satisfy the preset condition; determining resources allocated to the first service task from the first data twin resource pool based on the action information at the first time and response information corresponding to the action information.

5. The method of claim 4, wherein, The method further comprises: obtaining a DTN network state at a second time after the first time after the first service task is executed.

6. The method of claim 4 or 5, wherein the DTN network state comprises a vector of digital twin resource states and service demands, and the digital twin resource states comprise at least one of: a data twin (DT) position, used to represent an edge server to which a data twin corresponding to a service task belongs; a DT availability, used to represent validity or invalidity of the service task; an edge DT resource quantity, used to represent a quantity of hardware resources and twin resources.

7. The method of any one of claims 4 to 6, wherein the response information is a function of service revenue and service cost of the first service task, and the response information comprises at least one of: a difference between the service revenue and the service cost of the first service task; a weighted sum of the service revenue and the service cost of the first service task, wherein the service cost comprises at least one of a DT synchronization cost, a DT orchestration cost, and a server operation cost.

8. The method according to any one of claims 4 to 7, characterized in that, The method further comprises at least one of: acquire DTN state information and response information from a digital twin network (DTN) in real time; acquire historical DTN state information and historical response information from an edge server that executes the first service task.

9. The method according to any one of claims 1 to 8, characterized in that, The method further comprises at least one of: register a VDT for the first service request; periodically collect service information and resource information of the service information; clean up the VDT when all DTs managed by the VDT are executed; determine resource allocation of all DTs managed by the VDT; determine a digital twin resource usage strategy for executing the first service request according to a business operation process.

10. A first device, comprising: comprise a processing module configured to: determine a first data twin resource pool corresponding to the first service request, the first service request corresponding to a first service task; determine an agent on the first data twin resource pool; execute the first service task by the agent and determine resources allocated to the first service task from the first data twin resource pool.

11. A communication device, wherein, comprise: a transceiver; a memory; a processor connected to the transceiver and the memory respectively, configured to control wireless signal transceiving of the transceiver by executing computer executable instructions on the memory, and capable of implementing the method of any one of claims 1-9.

12. A computer storage medium, wherein, The computer storage medium stores computer executable instructions; the computer executable instructions are executed by the processor, and capable of implementing the method of any one of claims 1-9.

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