Resource deployment method, resource deployment equipment, storage medium and computer product

Abstract

The invention discloses a resource deployment method, resource deployment equipment, a storage medium and a computer product, and the method comprises the steps: obtaining the resource state information of network nodes and the user task request state information of a terminal, the network nodes comprise inherent nodes in a network and temporary nodes in the network, the temporary nodes comprise one or more of the following nodes: temporary air nodes and temporary ground nodes; based on the resource state information of the inherent node and the user task request state information, a task switching unloading strategy is determined, and the task switching unloading strategy comprises one or more of the following steps: unloading the task to the inherent node, unloading the task to a temporary ground node, and unloading the task to the temporary ground node by using a temporary air node relay; and calling a network node contained in the task switching unloading strategy, and allocating corresponding resources to the terminal to execute a corresponding task.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a resource deployment method, a resource deployment device, a storage medium, and a computer product. Background Art

[0002] The continuous development of new applications such as virtual reality, metaverse and autonomous driving has brought about a surge in traffic load. Traffic load has a tidal effect in time and space. During a specific period of time, a large number of terminals may be connected to the region, generating burst traffic, which poses severe challenges to the communication and computing processing of the network. On the one hand, the computing power and storage space of the terminal are usually limited, and it is difficult and costly to complete local computing tasks; on the other hand, the amount of data in burst traffic far exceeds the traffic in other periods, causing serious tension in the communication and computing resources of base stations, edge cloud servers, etc. in the region, making it difficult to quickly meet the business needs of a large number of terminals (such as latency, energy consumption, reliability, etc.).

[0003] In response to sudden high traffic loads in the region, the cost of expanding the computing power of network base stations or edge cloud servers is high. Summary of the invention

[0004] Embodiments of the present application provide a resource deployment method, a resource deployment device, a storage medium, and a computer product.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] The present invention provides a method for resource deployment, which includes:

[0007] Acquire resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary aerial nodes and temporary ground nodes;

[0008] Determine a task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary aerial node;

[0009] The network nodes included in the task switching offloading strategy are called to allocate corresponding resources to the terminal to execute the corresponding tasks.

[0010] In the above solution, determining the task switching offloading strategy based on the resource status information of the inherent node and the user task request status information includes:

[0011] Determining a maximum computing load that the inherent node can bear based on the resource status information of the inherent node and the user task request status information;

[0012] Based on the maximum computing load, a task switching offloading strategy is determined.

[0013] In the above scheme, the resource status information includes: communication resource status information and computing resource status information, wherein the communication resource status information includes one or more of the following: bandwidth, power, channel status information, data transmission rate; the computing resource status information includes one or more of the following: number of cores / frequency of the processor, memory size, computing energy consumption per bit / per unit time;

[0014] The user task request status information includes: the data volume of the task request, the delay requirement, and the requirements for computing power and storage space.

[0015] In the above scheme, the task switching offloading strategy includes offloading the task to the inherent node, and the calling of the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task includes:

[0016] Calling the intrinsic node to construct one or more questions;

[0017] Calling the inherent node to solve the one or more problems to obtain solutions to the one or more problems;

[0018] Calling the intrinsic node to allocate corresponding resources to the terminal based on the solutions of the one or more problems;

[0019] The one or more problems include: constructing a throughput maximization problem with bandwidth and the number of cores / frequency of the processor as variables and communication resources, computing resources and latency requirements as constraints;

[0020] A delay minimization problem with the bandwidth and the number of cores / frequency of the processor as variables and the communication resources, the computing resources and the amount of data requested by the task as constraints;

[0021] An energy efficiency minimization / maximization problem with the bandwidth, the number of cores / frequency of the processor, and the amount of data unloaded by the terminal as variables, and the communication resources, the computing resources, and the latency requirements as constraints.

[0022] In the above scheme, the task switching offloading strategy includes one or more of the following: offloading the task to the temporary ground node, offloading the task to the temporary ground node by relaying the temporary aerial node, and calling the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task, including:

[0023] Determine an initial deployment position of the temporary ground node, a first terminal set and a second terminal set to be unloaded to the temporary ground node, wherein the first terminal set includes terminals that are directly unloaded to the temporary ground node, and the second terminal set includes terminals that are relay unloaded based on the temporary aerial node;

[0024] Calling the temporary ground node, and allocating corresponding resources to the terminals in the first terminal set to perform corresponding tasks based on the initial deployment position and the trajectory of the temporary ground node;

[0025] The temporary ground node is called, and based on the moving trajectory of the temporary aerial node and the trajectory of the temporary ground node, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0026] In the above solution, determining the initial deployment position of the temporary ground node includes:

[0027] Determining a set of deployable locations based on the deployable range information and mobility restriction information of the temporary ground node;

[0028] A position with the largest average throughput in the set of deployable positions is determined as the initial deployment position.

[0029] In the above solution, the calling of the temporary ground node and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node include:

[0030] If the movable range of the temporary ground node belongs to the first movable range, the first iterative algorithm is executed:

[0031] Based on the initial deployment position, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the movement trajectory, the communication resource allocation mode and the computing resource allocation mode of the temporary aerial node are optimized and solved to obtain the resource allocation mode; the movable distance included in the first moving range is less than the distance threshold;

[0032] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0033] In the above solution, the calling of the temporary ground node and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node include:

[0034] If the movable range of the temporary ground node belongs to the second movable range, the second iterative algorithm is executed:

[0035] Based on the initial deployment position, the movable range, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the second movable range is greater than the distance threshold;

[0036] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0037] The embodiment of the present application provides a resource deployment device, including: a communication interface and a processor; wherein:

[0038] The processor is used to: obtain resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary air nodes and temporary ground nodes;

[0039] The processor is used to: determine a task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary aerial node;

[0040] The processor is used to call the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to execute the corresponding task.

[0041] An embodiment of the present application further provides a storage medium on which a computer program is stored, wherein the computer program implements the steps of any of the above methods when executed by a processor.

[0042] An embodiment of the present application further provides a computer product, including a computer program, which implements the steps of any of the above methods when executed by a processor.

[0043] The embodiment of the present application provides a resource deployment method, a resource deployment device, a storage medium and a computer product, the method comprising: obtaining resource status information of a network node and user task request status information of a terminal, wherein the network node comprises an inherent node in the network and a temporary node in the network, and the temporary node comprises one or more of the following: a temporary aerial node and a temporary ground node; based on the resource status information of the inherent node and the user task request status information, determining a task switching offloading strategy, wherein the task switching offloading strategy comprises one or more of the following: offloading the task to an inherent node, offloading the task to a temporary ground node, and offloading the task to a temporary ground node using a temporary aerial node relay; calling the network nodes included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task; the present application implements communication and computing resource scheduling based on the task switching offloading strategy, alleviating computing power shortages caused by bursty business traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a resource deployment method according to an embodiment of the present application;

[0045] Figure 2 A schematic diagram of a scenario of enhanced computing power coverage based on air-ground collaboration according to an embodiment of the present application;

[0046] Figure 3 A schematic diagram of a resource deployment architecture according to an embodiment of the present application;

[0047] Figure 4 A flowchart of a method for enhancing computing power coverage according to an embodiment of the present application;

[0048] Figure 5 A schematic diagram of a scenario in which computing power coverage is enhanced in a high-load V2X scenario according to an embodiment of the present application;

[0049] Figure 6 This is a schematic diagram of a high-load V2X air-ground collaborative interaction process in an embodiment of the present application;

[0050] Figure 7 A schematic diagram of a scenario of enhanced air-ground collaborative computing power coverage based on an O-RAN architecture according to an embodiment of the present application;

[0051] Figure 8 This is a schematic diagram of the structure of a resource deployment device according to an embodiment of the present application;

[0052] Fig. 9 A schematic diagram of the structure of a resource deployment device according to an embodiment of the present application. DETAILED DESCRIPTION

[0053] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0054] At present, in response to sudden high traffic loads in a region, the cost of expanding the computing power of network base stations or edge cloud servers is high and the energy efficiency is low. Related technologies propose the following solutions to alleviate the shortage of computing power.

[0055] 1. Deploy temporary ground computing power base stations, use idle terminals with strong computing power and endurance as temporary base stations, unload computing tasks to temporary base stations, and plan the location or trajectory of temporary base stations to provide communication and computing services on demand for each high-load area in different time periods. Existing ground temporary base stations are usually based on idle temporary computing resources, including mobile temporary computing resources and non-mobile temporary computing resources. Taking vehicles with idle computing power as an example, vehicles configured as dedicated base stations, vehicles in a parked state, and vehicles that are driving but have no perception or computing tasks can all be used as ground temporary computing power base stations; in addition, other terminals and servers with computing power can also be used as ground temporary computing power base stations.

[0056] However, this solution has the following problems: the coverage of temporary ground base stations is limited. Since burst traffic usually occurs in scenes where a large number of terminals gather, such as large gathering places and traffic congestion sections, the location and movement range of temporary ground computing power base stations are usually limited by the scene environment and traffic conditions, resulting in limited coverage. In addition, the height of temporary computing power base stations is relatively low, and the channel quality is easily affected by obstacles (such as buildings, trees, other vehicles, etc.), further reducing the coverage.

[0057] 2. Deploy temporary computing base stations in the air, such as unmanned aerial vehicles (UAVs) with computing capabilities, offload computing tasks to drones, and meet the QoS requirements of the business by planning the flight trajectory of the drones.

[0058] However, this solution has the following problems: the endurance and computing power of temporary aerial base stations are limited. Aerial computing base stations represented by unmanned aerial vehicles (UAVs) have the advantages of flexible flight routes and wide coverage, but their computing and endurance capabilities are relatively weak. In addition, the flight range of drones may also be limited due to management and control.

[0059] To this end, this application proposes a communication service processing method for high-load scenarios. The method is a computing power coverage enhancement solution based on air-ground joint assistance. The ground temporary computing power base station provides supplementary computing power, and the coverage range is expanded by drones. The computing power coverage is enhanced by jointly planning the deployment location and movement trajectory of air-ground temporary computing power base stations, and allocating communication resources and computing resources to alleviate the computing power shortage caused by sudden business traffic.

[0060] The present application embodiment provides a communication service processing method, which is applied to a resource deployment device, such as Figure 1As shown, the method includes:

[0061] Step 101: Obtain resource status information of network nodes and user task request status information of terminals, wherein network nodes include inherent nodes in the network and temporary nodes in the network, and temporary nodes include one or more of the following: temporary aerial nodes and temporary ground nodes.

[0062] In actual application, network nodes include one or more of the following: network-inherent computing nodes such as base stations and edge cloud servers, temporary aerial base stations UAVs with communication capabilities, temporary ground base stations (VBS) with both communication and computing capabilities, and user terminals that generate computing tasks.

[0063] In actual application, the inherent nodes in the network include inherent communication nodes and / or inherent computing nodes, and the temporary nodes in the network include temporary communication nodes and / or temporary computing nodes.

[0064] Step 102: Based on the resource status information of the inherent node and the user task request status information, determine the task switching offloading strategy, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to a temporary ground node, and offloading the task to a temporary ground node using a temporary aerial node relay.

[0065] In actual application, the above-mentioned inherent node resource status information and user task request status information belong to network perception information. This application formulates a task switching unloading strategy based on network perception information, including formulating a temporary resource deployment strategy and a communication computing resource scheduling strategy for inherent and temporary computing power base stations to adapt to the computing needs of high-load scenarios.

[0066] Step 103: calling the network nodes included in the task switching offloading strategy to allocate corresponding resources to the terminal to execute the corresponding task.

[0067] In actual application, this application calls the network nodes included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding tasks, thereby realizing communication and computing resource scheduling based on the task switching offloading strategy; this computing power coverage enhancement solution based on air-ground joint assistance uses temporary computing power base stations on the ground to provide supplementary computing power, and drones to expand coverage to alleviate computing power shortages caused by sudden business traffic.

[0068] A resource deployment method provided by an embodiment of the present application includes: obtaining resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary aerial nodes and temporary ground nodes; determining a task switching offloading strategy based on the resource status information of the inherent nodes and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node using a temporary aerial node relay; calling the network nodes included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task; the present application formulates a task switching offloading strategy based on network perception information, allocates corresponding resources to the terminal to perform the corresponding task, realizes communication and computing resource scheduling based on the task switching offloading strategy, and alleviates the computing power shortage caused by burst business traffic.

[0069] In some embodiments, step 102 determines the task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, including:

[0070] Determine the maximum computing load that the inherent node can bear based on the resource status information of the inherent node and the user task request status information;

[0071] Based on the maximum computational load, the task switching offloading strategy is determined.

[0072] In actual application, this application determines the task switching offloading strategy based on network perception information. It can calculate the maximum computing load that the inherent computing node can bear based on network perception information and formulate a task switching offloading strategy, that is, to determine which terminals' tasks can be offloaded to the inherent computing nodes and which terminals' tasks need to be switched to VBS.

[0073] In some embodiments, the resource status information includes: communication resource status information and computing resource status information, wherein the communication resource status information includes one or more of the following: bandwidth, power, channel status information, and data transmission rate; the computing resource status information includes one or more of the following: the number of cores / frequency of the processor (Central Processing Unit, CPU), memory size, and computing energy consumption per bit / per unit time;

[0074] User task request status information includes: the amount of data requested by the task, latency requirements, and requirements for computing power and storage space.

[0075] In some embodiments, the task switching offloading strategy includes offloading the task to a native node, and step 103 calls the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task, including:

[0076] Calling the intrinsic node to construct one or more questions;

[0077] Calling inherent nodes to solve one or more problems and obtain solutions to one or more problems;

[0078] Calling the inherent node to allocate corresponding resources to the terminal based on the solution of one or more problems;

[0079] One or more of the problems include: constructing a throughput maximization problem with bandwidth and number of processor cores / frequency as variables and communication resources, computing resources, and latency requirements as constraints;

[0080] The latency minimization problem with bandwidth, number of processor cores / frequency as variables and communication resources, computing resources and the amount of data requested by the task as constraints;

[0081] The energy efficiency minimization / maximization problem is solved with bandwidth, number of processor cores / frequency, and amount of data offloaded by the terminal as variables, and communication resources, computing resources, and latency requirements as constraints.

[0082] In practical applications, the task switching offloading decision problem can be modeled as a service terminal number maximization problem / throughput maximization problem based on communication, computing resource constraints and delay constraints.

[0083] In actual application, based on network perception information (task request information of the terminal, computing resources of the inherent base station, link quality, location, etc.), this application can model the task switching offloading decision problem as a problem of maximizing the number of service terminals / throughput maximization based on communication, computing resource constraints and delay constraints. By solving the above problems, the terminal set served by the inherent computing node can be determined, and the remaining terminals need to be switched to offload the computing tasks to the VBS. In other words, in the process of determining the task switching offloading strategy, this application takes into account that the overall performance of the network mainly depends on data transmission and computing, where the transmission performance is related to power, bandwidth, location distance, link quality, etc., and the computing performance depends on the available computing power of the computing node.

[0084] In some embodiments, the task switching offloading strategy includes one or more of the following: offloading the task to a temporary ground node, offloading the task to a temporary ground node by relaying a temporary aerial node, and step 103 calls the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task, including:

[0085] Determine an initial deployment position of a temporary ground node, a first terminal set to be unloaded to the temporary ground node, and a second terminal set, wherein the first terminal set includes terminals that are directly unloaded to the temporary ground node, and the second terminal set includes terminals that are relay unloaded based on the temporary aerial node;

[0086] Calling the temporary ground node, and allocating corresponding resources to the terminals in the first terminal set to perform corresponding tasks based on the initial deployment position and the trajectory of the temporary ground node;

[0087] The temporary ground node is called, and based on the moving trajectory of the temporary aerial node and the trajectory of the temporary ground node, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0088] For the terminal set that offloads tasks to VBS, the temporary computing power base station deployment scheduling module of this application realizes low-energy computing power coverage enhancement by jointly planning the UAV-VBS trajectory and resource allocation (communication, computing resource allocation) based on the communication, computing resources and deployment restrictions (deployment / moving range restrictions, UAV power, etc.) of VBS and UAV, as well as the location and task request status of each terminal, so as to provide computing services for more terminals.

[0089] In some embodiments, the above-mentioned determining the initial deployment position of the temporary ground node includes:

[0090] Based on the deployable range information and mobility restriction information of the temporary ground node, a deployable position set is determined; and a position with the largest average throughput in the deployable position set is determined as an initial deployment position.

[0091] Based on the deployable range and mobility restrictions of temporary ground nodes, this application determines a set of deployable locations, calculates the maximum throughput of each location in the set of deployable locations, and selects the location with the largest average throughput as the initial location. Further, based on this, appropriate communication and computing resources (bandwidth, CPU frequency, etc.) are allocated to the terminal that directly offloads tasks to the VBS.

[0092] In some embodiments, the calling of the temporary ground node and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node include:

[0093] If the movable range of the temporary ground node belongs to the first movable range, the first iterative algorithm is executed:

[0094] Based on the initial deployment position, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminal in the second terminal set, the movement trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the first moving range is less than the distance threshold;

[0095] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to execute corresponding tasks.

[0096] In actual application, the movable distance included in the first movable range is less than the distance threshold, indicating that the movable range of the VBS is small (for example, it can only be deployed near a few parking spots or the movable distance has no obvious effect on the channel quality of large-scale fading).

[0097] In actual application, based on the initial deployment position, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the movement trajectory of the temporary aerial node, the communication resource allocation method and the computing resource allocation method are optimized and solved to obtain the resource allocation method. Based on the resource allocation method, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks, including:

[0098] Based on the initial deployment position, fixed communication resources and computing resource allocation method, solving the movement trajectory of the temporary aerial node that maximizes energy efficiency;

[0099] Based on the initial deployment position, the movement trajectory of the temporary aerial node is fixed, and the communication resource and computing resource allocation method that maximizes energy efficiency is solved;

[0100] After multiple iterations, a solution that meets the solution conditions is selected from all solutions;

[0101] Based on the solution that meets the solution condition, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0102] In some embodiments, the calling of the temporary ground node and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node include:

[0103] If the movable range of the temporary ground node belongs to the second movable range, the second iterative algorithm is executed:

[0104] Based on the initial deployment position, the movable range, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the second movable range is greater than the distance threshold;

[0105] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to execute corresponding tasks.

[0106] In actual application, the movable distance included in the second movable range is greater than the distance threshold, indicating that the movable range of the VBS is large (the VBS can travel on a longer road section, and the movable distance affects the channel quality of large-scale fading).

[0107] In actual application, based on the initial deployment position, movable range, communication resource status information and computing status information of the temporary ground node, and task request status information of the terminals in the second terminal set, the movement trajectory of the temporary aerial node, the communication resource allocation method and the computing resource allocation method are optimized and solved to obtain the resource allocation method; the movable distance included in the second moving range is greater than the distance threshold; based on the resource allocation method, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks, including: based on the initial deployment position, fixed communication resources and computing resource allocation methods, solving the temporary aerial node movement trajectory and the temporary ground node movement trajectory that maximize energy efficiency;

[0108] Based on the initial deployment position, the movement trajectory of the temporary aerial node and the movement trajectory of the temporary ground node are fixed, and the communication resource and computing resource allocation method that maximizes energy efficiency is solved;

[0109] After multiple iterations, a solution that meets the solution conditions is selected from all solutions;

[0110] Based on the solution that meets the solution condition, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0111] In a feasible scenario of enhanced computing coverage based on air-ground collaboration, combined with Figure 2As shown. In the current period, the number of terminals in the base station coverage area is much higher than the average (which may be related to the gathering of people in shopping malls, traffic congestion during rush hour, etc.), and the terminals generate a large number of computing tasks, resulting in an explosion of computing load. Due to the limited computing power of the base station, it can only provide computing services for some terminals (terminals in area 1), and other terminals are provided with computing services by the ground temporary computing power base station (VBS refers to the ground temporary computing power base station in this embodiment). Among them, VBS can be an idle vehicle in a parking lot / parking space, or a vehicle in motion but with sufficient available computing resources, depending on the application scenario. Due to the low height of VBS, it is easily affected by buildings and trees, and the coverage range is limited. Therefore, for some terminals with poor link quality, UAV needs to be used for relaying to expand the computing power coverage of VBS. As Figure 2 As shown in the figure, area 2 is the terminal that can be directly served by VBS, that is, the link quality between such terminals and VBS is good, and the computing tasks can be directly offloaded to VBS; due to the obstruction of trees, other terminals need to be relayed and offloaded by UAV, thereby expanding the coverage of VBS to area 3.

[0112] In the above scenario, we can Figure 3 The architecture shown implements the computing power coverage enhancement method. Exemplarily, the architecture includes two parts: network information perception and resource deployment scheduling. The network information perception part collects information such as the communication computing resource status, task request status, location / trajectory of each node, energy (power) limit, etc. of the network; the resource deployment scheduling part formulates temporary resource deployment strategies and communication computing resource scheduling strategies for inherent and temporary computing power base stations based on the above perception information to adapt to the computing needs of high-load scenarios.

[0113] Among them, the resource deployment and scheduling part is composed of a task switching offloading decision module, an inherent computing node resource scheduling module and a temporary computing power base station deployment scheduling module (including multiple submodules). Among them, the task switching offloading decision module formulates a task switching offloading strategy based on the terminal's task request status, location and the available communication computing resources of the base station, that is, determines which terminals need to switch to the VBS for data calculation; further, based on the above switching offloading strategy, the inherent computing node resource scheduling module allocates appropriate communication (such as bandwidth, time slot, etc.) and computing resources (CPU / GPU frequency, storage space, etc.) to the terminal that is directly offloaded to the base station; for the terminal that offloads the task switch to the VBS, the submodules of the temporary computing power base station deployment scheduling module work together, according to the location and task request of the service terminal, comprehensively consider the deployment range limit of the VBS, the flight capability and endurance limit of the UAV, and jointly plan the two-dimensional / three-dimensional deployment location, movement trajectory and resource allocation of the UAV-VBS to maximize energy efficiency (the amount of data processed per unit energy consumption) to meet the QoS requirements of more terminal task requests.

[0114] In the above scenario, we can Figure 4 The process of the computing power coverage enhancement method shown in the figure determines the strategy and issues it:

[0115] Step S401: The network information sensing part senses the communication and computing resource status of the network nodes, the user task request status of the terminal and other information at a certain period.

[0116] Nodes include one or more of the following: network-specific computing nodes such as base stations and edge cloud servers, temporary aerial base stations UAVs with communication capabilities, temporary ground base stations VBSs with both communication and computing capabilities, and user terminals that generate computing tasks.

[0117] The communication resource status includes one or more of the following: bandwidth, power, channel status information, data transmission rate, etc.; the computing resource status includes one or more of the following: number of CPU cores / frequency, memory size, computing energy consumption per bit / time, etc.; the task request status includes one or more of the following: the amount of data requested by the task, latency requirements, requirements for computing power / storage space, etc.

[0118] Other information includes one or more of the following: location information and movement trajectory / range of each node, remaining power of the UAV / VBS, etc.

[0119] Step S402: The task switching offloading decision module formulates a task switching offloading strategy according to the link quality, the computing power of the inherent computing node and the task request status information.

[0120] In actual application, the task switching offloading decision module calculates the maximum computing load that the inherent computing node can bear based on the computing resources of the inherent computing node and the task request status information of the terminal's link quality, and formulates the task switching offloading strategy, that is, determines which terminals' tasks can be offloaded to the inherent computing node and which terminals' tasks need to be switched to the VBS.

[0121] Methods for formulating a task switching offloading strategy include one or more of the following.

[0122] (1) The overall performance of the network mainly depends on data transmission and computing. The transmission performance is related to power, bandwidth, location distance, link quality, etc., and the computing performance depends on the available computing power of the computing node. Therefore, based on network perception information (terminal task request information, inherent base station computing resources, link quality, location, etc.), the task switching offloading decision problem can be modeled as a problem of maximizing the number of service terminals / throughput maximization based on communication, computing resource constraints and delay constraints. By solving the above problem, the terminal set served by the inherent computing node can be determined, and the remaining terminals need to be switched to offload the computing tasks to the VBS.

[0123] (2) When the bandwidth and transmission power are constant, the transmission performance depends on the channel quality, which is the case if and only if the channel quality (reflected by distance or received power) is greater than the threshold (i.e. or P k h k ≥P thre ), the terminal can completely offload the data to the inherent computing node in a short time. Otherwise, when the channel quality is lower than the threshold due to long distance or obstacle obstruction, it is advisable to switch the task to VBS. Considering the limited computing power of the inherent computing node, for the terminals that meet the conditions, the “optimal” selection is made according to the channel quality, and a terminal set based on the inherent computing node base station offloading is constructed until the computing resources of the inherent base station are insufficient.

[0124] Step S403: The inherent computing node allocates appropriate communication and computing resources to the service terminal.

[0125] In actual application, based on the above task switching offloading strategy, the network further performs communication and computing resource scheduling. For terminals that do not need to be switched offloaded, the inherent computing node allocates appropriate communication and computing resources, including bandwidth, CPU frequency, etc., to the above terminals based on the task request status, power, link quality / distance and available communication computing resources of the inherent node of such terminals. The specific methods include one or more of the following.

[0126] (1) The problem is modeled as a throughput maximization problem with bandwidth and CPU frequency as variables and limited communication, computing resources and latency as constraints;

[0127] (2) The problem is modeled as a delay minimization problem with bandwidth and CPU frequency as variables and limited communication, computing resources, and the amount of data requested by the task as constraints;

[0128] (3) The problem is modeled as an energy efficiency minimization / maximization problem with bandwidth, CPU frequency, and the amount of data offloaded by the terminal as variables and limited communication, computing resources, and latency as constraints;

[0129] The above optimization problems can all be solved by conventional mathematical methods or machine learning (ML) to obtain resource allocation strategies.

[0130] For the terminal that needs to switch to VBS for task offloading, the resource deployment and scheduling method is performed according to step S404.

[0131] Step S404 includes step S4041-step S4043; step S404 involves that for the terminal set that unloads the task to the VBS, the temporary computing power base station deployment scheduling module implements low-energy computing power coverage enhancement by jointly planning the trajectory and resource allocation (communication, computing resource allocation) of the UAV-VBS according to the communication, computing resources and deployment restrictions (deployment / mobile range restrictions, UAV power, etc.) of the VBS and UAV, as well as the location and task request status of each terminal, and provides computing services for more terminals. The steps of deployment scheduling are as follows:

[0132] Step S4041: VBS comprehensively considers the terminal information and the deployable range and selects a suitable initial location.

[0133] Here, in order to reduce UAV energy consumption and unnecessary relay transmission of UAV, the VBS initial location selection module selects a suitable initial deployment location for VBS based on the link quality and task request information of each terminal, as well as the deployable range and communication computing resource status of VBS, so that more terminals can directly offload tasks to VBS and reduce the number / range of terminals served by UAV relay. The specific steps are as follows.

[0134] According to the deployment range restrictions of VBS (the length of the deployable road section, coordinates or the location of the deployable parking spot, etc.) and mobility restrictions (whether it can be moved, the maximum speed of movement, the starting and ending points of the road section, etc.), the initial deployable location set of VBS is determined, such as (x v ,y v )∈{(x 1 ,y 1 ),…,(x s ,y s )} or x v ∈[x 1 ,x S ],y v ∈[y 1 ,y S ];

[0135] Based on the method in step S403, the maximum throughput of each position in the above position set is calculated;

[0136] The location corresponding to the maximum throughput is selected as the initial deployment location of the VBS, and based on the result in 2), appropriate communication and computing resources (bandwidth, CPU frequency, etc.) are allocated to the terminal that directly offloads the task to the VBS.

[0137] Step S4042: The UAV comprehensively considers high coverage and power consumption and selects a suitable flight altitude.

[0138] Here, based on the initial deployment position of the VBS and other terminal information that needs to be relayed and unloaded based on the UAV (location and task request status information), the UAV flight altitude selection module comprehensively considers the impact of the flight altitude on the coverage range and power consumption, and determines the flight altitude of the UAV with the goal of maximizing the coverage range per unit energy consumption.

[0139] Step S4043: Based on the terminal location and task request and the resource constraints of the UAV-VBS, jointly optimize the movement trajectory of the UAV and VBS and the resource allocation of the UAV-VBS.

[0140] Here, based on the above-mentioned VBS initial position and UAV flight altitude, the UAV-VBS trajectory planning and resource scheduling modules work together to plan the UAV-VBS movement trajectory and communication and computing resource allocation methods, and use the UAV to assist the terminal that cannot be directly unloaded to relay the task to the VBS to meet the terminal's computing needs and maximize energy efficiency. The above problem can be modeled as an energy efficiency maximization problem with UAV-VBS position and bandwidth, computing resource allocation as variables, and latency, total resource constraints (bandwidth, CPU frequency, etc.), UAV and VBS energy constraints, and limited UAV and VBS mobile range as constraints, and solved by alternating optimization. Among them, energy efficiency is the throughput per unit energy consumption, and the throughput is related to the location and bandwidth allocation of the terminal, UAV, and VBS, and the energy consumption is related to the location, power, and communication computing resource allocation.

[0141] The solution methods include one or more of the following.

[0142] 1. When the VBS movable range is small (it can only be deployed near a few parking spots or the movable distance has no significant impact on the channel quality of large-scale fading), the steps of alternating optimization are as follows:

[0143] 1) Based on the initial position of the VBS in step S4041, the communication computing resource allocation method is fixed to solve the UAV movement trajectory that maximizes energy efficiency;

[0144] 2) Based on the initial position of the VBS in step S4041, the movement trajectory of the UAV is fixed, and a communication computing resource allocation method that maximizes energy efficiency is solved;

[0145] 3) Return to step 1) and iterate repeatedly until convergence.

[0146] 2. When the VBS movable range is large (VBS can travel on a long road section, and the movable distance has an impact on the channel quality of large-scale fading), the steps of alternating optimization are as follows:

[0147] 1) Based on the initial position of the VBS in step S4041, the communication computing resource allocation method is fixed to solve the movement trajectory of the UAV and the VBS that maximizes the energy efficiency;

[0148] 2) Fix the movement trajectories of UAV and VBS and find the communication computing resource allocation method that maximizes energy efficiency;

[0149] 3) Return to step 1) and iterate repeatedly until convergence.

[0150] 3. It can also be solved by reinforcement learning / deep learning, with environmental variables (the location of the terminal, UAV, and VBS, task request information, and available communication and computing resources) as input states, mobile location and communication and computing resource allocation as behaviors, and energy efficiency as the reward function, to train the ML model for the solution.

[0151] In a scenario where computing power coverage is enhanced in a feasible high-load V2X scenario, such as Figure 5 As shown in the figure, taking the high-load V2X scenario as an example, during the commuting peak, K vehicles enter the main road section, causing traffic congestion. The road section contains RSUs (for example, RSU1 and RSU2) and multiple parking spots (P), each of which has an idle vehicle. Among them, RSU, as a fixed base station, senses the information of each node in the network and provides communication and computing services for the terminal; the idle vehicles in the parking spots also have communication and computing capabilities and can be used as VBS. The vehicle uses the equipped sensors to sense the surrounding environment and generate task requests. Due to the limited computing power of the vehicle terminal, some tasks need to be offloaded to RSU or VBS. When unloading tasks, vehicle k will first unload the task to RSU. When the computing resources of RSU are insufficient or the link quality between RSU and vehicle k is poor, it will switch and unload the task to VBS. Since the height of VBS is lower than RSU, it is more susceptible to the influence of obstacles (such as buildings, trees, large buses, etc.). At this time, some vehicles need to perform relay unloading based on UAV.

[0152] The task processing process of vehicle k mainly includes three stages: data upload, data calculation and result feedback. Since the amount of data for result feedback is small, its transmission delay and energy consumption can be ignored. Therefore, the overall computing performance mainly depends on the task offloading transmission and calculation stages. The transmission rate depends on the bandwidth, power and link quality, among which the link quality mainly depends on large-scale fading (related to distance). When a traffic congestion scenario occurs, the vehicle moves slowly. Therefore, the position of the vehicle can be regarded as constant within time T (including N time slots). The calculation delay mainly depends on the allocated CPU frequency. In addition, since the energy consumption of the UAV is the lowest when flying at a constant speed, the UAV flies at a constant speed within a certain range and returns to the starting point after the task is completed. In order to complete the computing task of K vehicles within time T, the RSU needs to determine the terminal's task offloading strategy, the deployment method of the UAV-VBS, and the allocation method of existing communication computing resources based on the perceived network information. The process is as follows. Figure 6 shown. Figure 6 The steps for the high-load V2X air-ground collaborative interaction process are as follows:

[0153] Step 601: RSU collects network information at a certain period, including the location and task request status of K vehicles (data volume, latency, number of cycles required to calculate data, etc.), the flight range, battery power or endurance, bandwidth resources, transmission / computing energy consumption factor of UAV, the deployment / moving range, moving speed and available communication computing resources, transmission / computing energy consumption factor, etc. of VBS.

[0154] Step 602: The RSU calculates the maximum computing load that the RSU can bear based on the terminal location, task request status and the available communication computing resources of the RSU according to the method in step 602, and makes a task switching offloading decision accordingly. The task switching offloading decision includes: tasks of some terminals can be directly offloaded to the RSU (offloading decisions are sent to the corresponding terminals), and tasks of other terminals can be offloaded to the VBS (offloading decisions and related terminal information are sent to the VBS).

[0155] Step 603: For a terminal set that does not require switching offloading, the RSU allocates appropriate communication computing resources (bandwidth, CPU frequency, etc.) to the above terminals based on the location information of the terminals in the set, the task request status, and the available communication computing resources of the RSU according to the method in step 603.

[0156] Step 604: For the terminal set that needs to offload the task switching to the VBS, the VBS performs deployment scheduling based on the location of the terminals in the set, the task request status, and the energy, communication computing resources and other information of the UAV and VBS.

[0157] Here, first, determine the optimal parking space of the VBS, as well as the set of terminals that directly unload to the VBS and the bandwidth and CPU frequency allocated by the VBS to such terminals; further, determine the flight altitude of the UAV; finally, determine the flight trajectory of the UAV within time T, the bandwidth allocation method of the UAV, and the bandwidth and CPU frequency allocated by the VBS to the relay unloading terminals.

[0158] In a feasible scenario of enhanced air-ground collaborative computing power coverage based on O-RAN architecture, Figure 7 The interactive process for temporary base station deployment and scheduling based on O-RAN architecture, such as Figure 7 As shown, the process includes:

[0159] Step 701: A near real-time radio access network intelligent controller (Near-RT RIC) obtains the terminal task request status, power, link quality, and communication computing resource status of the VBS and the base station.

[0160] Here, the Near-RT RIC subscribes to the task request status, link quality, power and other data of all user terminals within the cell range, as well as the communication computing resource information of the base station and VBS from the base station / E2 Node through the E2 interface; and obtains the application-side location / trajectory data of the terminals within the cell range, the location information of the base station, the mobility information of the VBS (deployable range, moving speed, etc.) and the UAV mobility (flight range, flight speed, power consumption, etc.) information from the Non-RT RIC through the A1 interface.

[0161] Step 702: Near-RT RIC formulates a task switching offloading strategy based on the link quality of the terminal, the task request status, and the computing resources of the base station / VBS, and sends the terminal information (task request status, location, link quality, etc.) offloaded based on the base station and VBS to the base station and VBS respectively through the E2 interface.

[0162] Step 703: The base station allocates appropriate communication computing resources to the terminal that is directly offloaded to the base station according to the sent task list information and the available resource status, and sends the policy to the corresponding terminal.

[0163] Step 704: Near-RT RIC determines the initial deployment location of the VBS and the flight altitude of the UAV according to the above-mentioned task switching offloading strategy, based on the terminal information switched to the VBS for task offloading, the available communication computing resources of the VBS, and the mobility information of the UAV and the VBS, and sends the decision result to the VBS and the UAV.

[0164] Step 705: VBS jointly plans the movement trajectory and communication and computing resource allocation method of UAV-VBS based on the sent task list information and the location / trajectory of the corresponding terminal and the available resource status, clarifies the terminal's switching unloading method (directly unloading to VBS or unloading to VBS based on UAV relay), and sends the above switching unloading method to the corresponding terminal.

[0165] Finally, the terminal offloads tasks according to the specified offloading strategy, and the communication and computing nodes allocate resources to execute the computing tasks of the terminal according to the specified deployment scheduling method.

[0166] From the above, it can be seen that the present application proposes a method for enhancing computing power coverage based on air-ground collaboration. Both the ground temporary computing power base station and the aerial relay UAV are mobile, including the dynamics of the optional nodes (initial deployment position) and the mobility of the subsequent trajectory. The appropriate deployment position and moving trajectory (two-dimensional ground temporary computing power base station, three-dimensional UAV) can be selected according to business needs and scenario characteristics to achieve flexible coverage enhancement of computing power.

[0167] This application proposes a VBS location selection scheme and a computing-oriented control decision scheme for VBS when the mobility of VBS is limited, including a location deployment strategy for ground temporary computing power base stations, a task offloading strategy based on ground temporary base stations, a UAV three-dimensional trajectory planning strategy, and a UAV-VBS joint communication computing resource allocation strategy.

[0168] The present application proposes a UAV-VBS joint trajectory planning scheme and a corresponding task offloading decision and communication computing resource allocation scheme for when the VBS has strong mobility, including a location deployment strategy for a temporary ground computing power base station, a task offloading strategy based on a temporary ground computing power base station, a UAV-VBS joint dynamic location planning strategy, and a corresponding communication computing resource allocation strategy based on a dynamic UAV-VBS location.

[0169] It should be noted that compared with the fixed-location ground base station / server deployment solution in the related art, this application is more adaptable to differentiated scenarios and business needs, and covers a larger number of terminals. In addition, the collaboration between the UAV mobile relay platform and the temporary ground computing power base station further expands the computing power coverage;

[0170] It should be noted that compared with the UAV-based aerial computing base station in the related technology, the present application consumes less power for the UAV, the temporary base station works longer, and has higher energy efficiency.

[0171] This application proposes two temporary base station deployment and resource scheduling solutions based on the impact of scenario characteristics on the deployment range / mobility of temporary computing power base stations on the ground, which can better achieve on-demand deployment and on-demand scheduling to meet the computing needs in high-load scenarios. This application proposes a three-dimensional trajectory planning solution for UAVs, which uses the characteristics of UAVs and plans the height and two-dimensional plane trajectory of UAVs to achieve comprehensive optimization of UAV coverage and energy consumption.

[0172] The present application also provides a resource deployment device, such as Figure 8 As shown, the resource deployment device includes:

[0173] The acquisition module 801 is used to acquire resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary air nodes and temporary ground nodes;

[0174] The processing module 802 is used to determine the task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary air node;

[0175] The processing module 802 is used to call the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to execute the corresponding task.

[0176] In some embodiments, the processing module 802 is used to determine the maximum computing load that the inherent node can bear based on the resource status information of the inherent node and the user task request status information; and determine the task switching offloading strategy based on the maximum computing load.

[0177] In some embodiments, resource status information includes: communication resource status information and computing resource status information, wherein the communication resource status information includes one or more of the following: bandwidth, power, channel status information, and data transmission rate; the computing resource status information includes one or more of the following: the number of processor cores / frequency, memory size, and computing energy consumption per bit / unit time; the user task request status information includes: the amount of data requested by the task, latency requirements, and requirements for computing power and storage space.

[0178] In some embodiments, the processing module 802 is used to call the inherent node to construct one or more questions;

[0179] Calling inherent nodes to solve one or more problems and obtain solutions to one or more problems;

[0180] Calling the inherent node to allocate corresponding resources to the terminal based on the solution of one or more problems;

[0181] One or more of the problems include: constructing a throughput maximization problem with bandwidth and number of processor cores / frequency as variables and communication resources, computing resources, and latency requirements as constraints;

[0182] The latency minimization problem with bandwidth, number of processor cores / frequency as variables and communication resources, computing resources and the amount of data requested by the task as constraints;

[0183] The energy efficiency minimization / maximization problem is solved with bandwidth, number of processor cores / frequency, and amount of data offloaded by the terminal as variables, and communication resources, computing resources, and latency requirements as constraints.

[0184] In some embodiments, the task switching offloading strategy includes one or more of the following: offloading the task to a temporary ground node, offloading the task to a temporary ground node by relaying a temporary aerial node; a processing module 802 is used to determine an initial deployment position of the temporary ground node, a first terminal set to be offloaded to the temporary ground node, and a second terminal set, wherein the first terminal set includes terminals that are directly offloaded to the temporary ground node, and the second terminal set includes terminals that are relayed offloaded based on the temporary aerial node;

[0185] Calling the temporary ground node, and allocating corresponding resources to the terminals in the first terminal set to perform corresponding tasks based on the initial deployment position and the trajectory of the temporary ground node;

[0186] The temporary ground node is called, and based on the moving trajectory of the temporary aerial node and the trajectory of the temporary ground node, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0187] In some embodiments, the processing module 802 is used to determine a set of deployable positions based on the deployable range information and mobility restriction information of the temporary ground node; and determine the position with the largest average throughput in the set of deployable positions as the initial deployment position.

[0188] In some embodiments, the processing module 802 is used to execute a first iterative algorithm if the movable range of the temporary ground node belongs to the first movable range: based on the initial deployment position, the communication resource status information and computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, communication resource allocation method and computing resource allocation method of the temporary aerial node are optimized and solved to obtain a resource allocation method; the movable distance included in the first movable range is less than the distance threshold; based on the resource allocation method, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0189] In some embodiments, the processing module 802 is used to execute a second iterative algorithm if the movable range of the temporary ground node belongs to the second movable range: based on the initial deployment position, the movable range, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the second movable range is greater than the distance threshold; based on the resource allocation method, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0190] The present application also provides a resource deployment device, such as Fig. 9 As shown, the resource deployment device 900 includes: a communication interface 901 and a processor 902; wherein,

[0191] Communication interface 901, capable of exchanging information with other devices;

[0192] The processor 902 is connected to the communication interface 901 and is used to execute the method provided by one or more technical solutions on the terminal side when running the computer program;

[0193] The memory 903 stores computer programs that can be executed on the processor 902 .

[0194] The processor 902 is used to obtain resource status information of network nodes and user task request status information of the terminal, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary air nodes and temporary ground nodes;

[0195] Determine the task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary aerial node;

[0196] The network nodes included in the task switching offloading strategy are called to allocate corresponding resources to the terminal to execute the corresponding tasks.

[0197] In some embodiments, the processor 902 is used to determine the maximum computing load that the inherent node can bear based on the resource status information of the inherent node and the user task request status information; and determine the task switching offloading strategy based on the maximum computing load.

[0198] In some embodiments, resource status information includes: communication resource status information and computing resource status information, wherein the communication resource status information includes one or more of the following: bandwidth, power, channel status information, and data transmission rate; the computing resource status information includes one or more of the following: the number of processor cores / frequency, memory size, and computing energy consumption per bit / unit time; the user task request status information includes: the amount of data requested by the task, latency requirements, and requirements for computing power and storage space.

[0199] In some embodiments, the processor 902 is configured to call an intrinsic node to construct one or more questions;

[0200] Calling inherent nodes to solve one or more problems and obtain solutions to one or more problems;

[0201] Calling the inherent node to allocate corresponding resources to the terminal based on the solution of one or more problems;

[0202] One or more of the problems include: constructing a throughput maximization problem with bandwidth and number of processor cores / frequency as variables and communication resources, computing resources, and latency requirements as constraints;

[0203] The latency minimization problem with bandwidth, number of processor cores / frequency as variables and communication resources, computing resources and the amount of data requested by the task as constraints;

[0204] The energy efficiency minimization / maximization problem is solved with bandwidth, number of processor cores / frequency, and amount of data offloaded by the terminal as variables, and communication resources, computing resources, and latency requirements as constraints.

[0205] In some embodiments, the task switching offloading strategy includes one or more of the following: offloading the task to a temporary ground node, offloading the task to a temporary ground node by relaying a temporary aerial node, the processor 902 is used to determine the initial deployment position of the temporary ground node, the first terminal set to be offloaded to the temporary ground node, and the second terminal set, wherein the first terminal set includes terminals that are directly offloaded to the temporary ground node, and the second terminal set includes terminals that are relayed offloaded based on the temporary aerial node;

[0206] Calling the temporary ground node, and allocating corresponding resources to the terminals in the first terminal set to perform corresponding tasks based on the initial deployment position and the trajectory of the temporary ground node;

[0207] The temporary ground node is called, and based on the moving trajectory of the temporary aerial node and the trajectory of the temporary ground node, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

[0208] In some embodiments, the processor 902 is used to determine a set of deployable positions based on the deployable range information and mobility restriction information of the temporary ground node; and determine the position with the largest average throughput in the set of deployable positions as the initial deployment position.

[0209] In some embodiments, the processor 902 is configured to execute a first iterative algorithm if the movable range of the temporary ground node belongs to the first movable range:

[0210] Based on the initial deployment position, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminal in the second terminal set, the movement trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the first moving range is less than the distance threshold;

[0211] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to execute corresponding tasks.

[0212] In some embodiments, the processor 902 is configured to execute a second iterative algorithm if the movable range of the temporary ground node belongs to the second movable range:

[0213] Based on the initial deployment position, the movable range, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the second movable range is greater than the distance threshold;

[0214] Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to execute corresponding tasks.

[0215] It should be noted that the specific processing process of the communication interface 901 and the processor 902 can be understood by referring to the above method, which will not be repeated here.

[0216] Of course, in actual application, the various components in the resource deployment device 900 are coupled together through the bus system 904. It can be understood that the bus system 904 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 904 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig. 9 Various buses are labeled as bus system 904.

[0217] The memory 903 in the embodiment of the present application is used to store various types of data to support the operation of the resource deployment device 900. Examples of such data include: any computer program used to operate on the resource deployment device 900.

[0218] The method disclosed in the above embodiment of the present application can be applied to the processor 902, or implemented by the processor 902. The processor 902 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 902. The above processor 902 may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 902 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 903, and the processor 902 reads the information in the memory 903 and completes the steps of the above method in combination with its hardware.

[0219] In an exemplary embodiment, the resource deployment device 900 can be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0220] In an exemplary embodiment, the network device may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0221] In an exemplary embodiment, the user terminal may be implemented by one or more ASICs, DSPs, PLDs, CPLDs, FPGAs, general purpose processors, controllers, MCUs, microprocessors, or other electronic components to perform the aforementioned methods.

[0222] It can be understood that the memory of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (FlashMemory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Sync Link Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0223] In an exemplary embodiment, the embodiment of the present application further provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, for example, a memory 903 storing a computer program, and the computer program can be executed by a processor 902 of a resource deployment device 900 to complete the steps of the above method on the terminal side. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0224] In an exemplary embodiment, the embodiment of the present application further provides a computer program product, which, when executed by one or more computing devices, executes any of the aforementioned methods for generating a digital twin network. The computer program product may be a software installation package, and when any of the aforementioned methods for generating a digital twin network is required, the computer program product may be downloaded and executed on a computer.

[0225] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0226] In addition, the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0227] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A resource deployment method, characterized in that: include: Acquire resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary aerial nodes and temporary ground nodes; Determine a task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary aerial node; The network nodes included in the task switching offloading strategy are called to allocate corresponding resources to the terminal to execute the corresponding tasks.

2. The method according to claim 1, characterized in that The determining of the task switching offloading strategy based on the resource status information of the inherent node and the user task request status information includes: Determining a maximum computing load that the inherent node can bear based on the resource status information of the inherent node and the user task request status information; Based on the maximum computing load, a task switching offloading strategy is determined.

3. The method according to claim 1, characterized in that The resource status information includes: communication resource status information and computing resource status information, wherein the communication resource status information includes one or more of the following: bandwidth, power, channel status information, and data transmission rate; the computing resource status information includes one or more of the following: number of cores / frequency of the processor, memory size, and computing energy consumption per bit / per unit time; The user task request status information includes: the data volume of the task request, the delay requirement, and the requirements for computing power and storage space.

4. The method according to claim 1, characterized in that The task switching offloading strategy includes offloading the task to the inherent node, and calling the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task includes: Calling the intrinsic node to construct one or more questions; Calling the inherent node to solve the one or more problems to obtain solutions to the one or more problems; Calling the intrinsic node to allocate corresponding resources to the terminal based on the solutions of the one or more problems; The one or more problems include: constructing a throughput maximization problem with bandwidth and the number of cores / frequency of the processor as variables and communication resources, computing resources and latency requirements as constraints; A delay minimization problem with the bandwidth and the number of cores / frequency of the processor as variables and the communication resources, the computing resources and the amount of data requested by the task as constraints; An energy efficiency minimization / maximization problem with the bandwidth, the number of cores / frequency of the processor, and the amount of data unloaded by the terminal as variables, and the communication resources, the computing resources, and the latency requirements as constraints.

5. The method according to claim 1, characterized in that The task switching offloading strategy includes one or more of the following: offloading the task to the temporary ground node, offloading the task to the temporary ground node by relaying the temporary aerial node, and calling the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to perform the corresponding task, including: Determine an initial deployment position of the temporary ground node, a first terminal set and a second terminal set to be unloaded to the temporary ground node, wherein the first terminal set includes terminals that are directly unloaded to the temporary ground node, and the second terminal set includes terminals that are relay unloaded based on the temporary aerial node; Calling the temporary ground node, and allocating corresponding resources to the terminals in the first terminal set to perform corresponding tasks based on the initial deployment position and the trajectory of the temporary ground node; The temporary ground node is called, and based on the moving trajectory of the temporary aerial node and the trajectory of the temporary ground node, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

6. The method according to claim 5, characterized in that The determining of the initial deployment position of the temporary ground node comprises: Determining a set of deployable locations based on the deployable range information and mobility restriction information of the temporary ground node; A position with the largest average throughput in the set of deployable positions is determined as the initial deployment position.

7. The method according to claim 5, characterized in that The calling of the temporary ground node, and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node, includes: If the movable range of the temporary ground node belongs to the first movable range, the first iterative algorithm is executed: Based on the initial deployment position, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the movement trajectory, the communication resource allocation mode and the computing resource allocation mode of the temporary aerial node are optimized and solved to obtain the resource allocation mode; the movable distance included in the first moving range is less than the distance threshold; Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

8. The method according to claim 5, characterized in that The calling of the temporary ground node, and allocating corresponding resources to the terminals in the second terminal set to perform corresponding tasks based on the moving trajectory of the temporary aerial node, includes: If the movable range of the temporary ground node belongs to the second movable range, the second iterative algorithm is executed: Based on the initial deployment position, the movable range, the communication resource status information and the computing status information of the temporary ground node, and the task request status information of the terminals in the second terminal set, the moving trajectory, the communication resource allocation method and the computing resource allocation method of the temporary aerial node are optimized and solved to obtain the resource allocation method; the movable distance included in the second movable range is greater than the distance threshold; Based on the resource allocation mode, corresponding resources are allocated to the terminals in the second terminal set to perform corresponding tasks.

9. A resource deployment device, characterized in that: include: A communication interface and a processor; wherein, The processor is used to: obtain resource status information of network nodes and user task request status information of terminals, wherein the network nodes include inherent nodes in the network and temporary nodes in the network, and the temporary nodes include one or more of the following: temporary air nodes and temporary ground nodes; The processor is used to: determine a task switching offloading strategy based on the resource status information of the inherent node and the user task request status information, wherein the task switching offloading strategy includes one or more of the following: offloading the task to the inherent node, offloading the task to the temporary ground node, and offloading the task to the temporary ground node by relaying the temporary aerial node; The processor is used to call the network node included in the task switching offloading strategy to allocate corresponding resources to the terminal to execute the corresponding task.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

11. A computer product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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