CN-122002297-A - 6G space-world integrated network resource allocation device based on evolution game

Abstract

The invention discloses a 6G space-earth integrated network resource allocation device based on an evolution game, and belongs to the technical field of calculation, calculation or counting. The device considers the problems that a plurality of tasks in a 6G space-time integrated network compete for limited computing resources at the same time, so that the resource allocation is unbalanced, the task processing delay is increased and the like, and provides a device for solving the task unloading and the resource allocation of an edge server so as to meet the requirements of ground users on the tasks. The device firstly builds a 6G space-time integrated calculation unloading network model, secondly defines an optimization target and constraint conditions for minimizing task execution time delay, and finally provides a method for solving task unloading and resource allocation problems by adopting a combined task unloading and resource allocation algorithm. Simulation results show that the proposed algorithm has better network performance.

Inventors

• ZHANG YUEXIA
• WANG XINYI

Assignees

• 北京信息科技大学

Dates

Publication Date

20260508

Application Date

20241104

Claims (4)

1. 1. The method for establishing the 6G space-earth integrated network resource allocation device based on the evolution game is characterized by comprising the following steps of: 1) Constructing a 6G space-earth integrated calculation unloading network model; 2) Defining an optimization target and constraint conditions for minimizing task execution delay; 3) And solving the task unloading and resource allocation problems by adopting a combined task unloading and resource allocation algorithm.
2. 2. The device for establishing the evolution game-based 6G space-time integrated network resource allocation according to claim 1, wherein the 6G space-time integrated calculation unloading network model is constructed in the step 1), and comprises three layers of networks, namely a space-based network, a space-based network and a foundation network; the space-based network comprises M Unmanned Aerial Vehicles (UAVs) on which a communication module and an edge server are configured, wherein the UAS set can be expressed as UAS= { UAS 1 ,UAS 2 ,...,UAS m ,...,UAS M |m∈M},UAS m for an mth UAV, the effective communication radius of the UAS is expressed as r UAS , the communication/calculation service can be provided for the user equipment, the ground-based network comprises I user equipment (USE) and J Base Stations (BS), each BS is provided with the edge server, wherein the USE set can be expressed as USE= { USE 1 ,USE 2 ,...,USE i ,...,USE 1 |i E I }, USE i is expressed as I user equipment, the effective communication radius of the USE is expressed as r USE (r UAS >r BS >r USE ), and the effective communication radius of the UAS can be expressed as UAS= { UAS 1 ,UAS 2 ,...,UAS m ,...,UAS M |m∈M},UAS m for an M UAV, the effective communication radius of the UAS is expressed as r UAS , the communication/calculation service can be provided for the user equipment, and J Base Stations (BS) each of which is provided with the edge server, and the USE set can be expressed as USE 1 ,USE 2 ,...,USE i ,...,USE 1 |i }, wherein the USE i is expressed as USE= { USE and J is expressed as J35, and J is expressed as j|35; In this network model, only USE will spontaneously generate computational tasks, STS, BS and UAS can only perform tasks but will not spontaneously generate computational tasks, USE i in each time slot generates a computational task to be processed, the task can be represented by a triplet < D i ,C i ,T i max >, D i represents the task data size, C i represents the task calculation, i.e. the computational resources required for completing the task, T i max represents the maximum acceptable task completion time, USE i can offload tasks to edge servers of each network area for processing, USE i can offload tasks to STS for execution in the sky base area through USE-STS communication links, USE i can offload tasks to UAS for execution through USE-UAS communication links, USE i can offload tasks to BS for execution through USE-BS communication links in the ground base area, and the task execution delay consists of transmission delay and processing delay.
3. 3. The device for establishing the evolution game-based 6G space-time integrated network resource allocation according to claim 1, wherein in the step 2), an optimization target and constraint conditions for minimizing task execution delay are defined, a calculation unloading process in a 6G SAG-CO network model is studied by taking USE as a center, and further interference conditions in a USE communication process are discussed, namely firstly, the condition that interference exists between USE-BS and USE-UAS communication links is considered, secondly, interference also exists between STS-STS, UAS-UAS and BS-BS communication links, but different frequency bands are divided from USE transmission links; The tasks generated by the USE are offloaded to the STS server over the wireless channel to perform tasks, and the channel gain for the information transfer between USE i and STS n can be expressed as: Where v i,n represents the complex Gaussian variable of Rayleigh (Rayleigh) fading, ε i,n represents the shadow fading subject to lognormal distribution, d i,n represents the distance between USE i and STS n , Representing a path loss index; The communication between USE and STS adopts Ka frequency band, and has no mutual interference problem with other frequency bands, and the achievable task transmission rate from USE i to STS n is expressed as: Wherein B i represents the channel bandwidth of USE i , p i represents the transmit power of USE i , σ 2 represents gaussian white noise; The communication links between UAS and BS share the same frequency band as USE-UAS, and the signal-to-interference-and-noise ratio γ i,m from USE i to UAS m is expressed as: Wherein, the Representing the number of USE's that offload tasks to UAS m within USE i communication range; Representing interference caused by other USE-UAS communication links, G i.m represents the channel between USE i and UAS m , assuming that the position of the UAS is quasi-fixed, i.e., the UAS is in a hover state, the channel between USE i and UAS m can be constructed as a rice (Rician) fading channel model, expressed as: Wherein, the Represents the line of sight (LoS) channel component, d i,m represents the distance between USE i to UAS m , lambda represents the Rician factor, Represents the path loss index of LoS in Rician fading, |g i,m |=1 represents the LoS channel coefficient; represents the non line of sight (NLoS) channel component, g i,m represents the NLoS channel coefficient represented by the zero mean unit variance gaussian fading channel, Representing the path loss index of NLoS in Rician fading, and thus the achievable task transmission rates for USE i to UAS m are expressed as: R i,m ＝B i log 2 (1+γ i,m ) (5) USE can offload tasks to BS, USE i receives signal to noise ratio of base station BS j as: Wherein, the Representing interference caused by other USE-BS links, G i,j represents the channel between USE i and BS j , expressed as: Where g 0 denotes the channel power gain at reference distance d 0 =1, d i,j denotes the distance between USE i and BS j , and thus the achievable task transmission rate of USE i to BS j is expressed as: R i,j ＝B i log 2 (1+λ i,j ) (8) When USE i offloads a computational task to STS n , the computational task is transmitted over a wireless channel to a transmission delay on an STS server Can be expressed as: Processing delay required for processing tasks on STS edge server Expressed as: Wherein f i,n denotes the computing resources allocated to the task by the STS; thus, when a task is offloaded onto the STS n server, the execution latency of the task can be expressed by the formula: Wherein, the Representing binary decisions when The time represents processing tasks on STS n servers; indicating that the task is not offloaded to STS n server; When USE i offloads a computational task to UAS m , the computational task is delayed in its transmission over the wireless channel Can be expressed as: Processing delay required for processing tasks on UAS edge servers Expressed as: Wherein f i,u denotes the computational resources allocated to the task by the UAS; thus, when a task is offloaded onto the UAS m server, the execution latency of the task can be expressed by the formula: Wherein, the Representing binary decisions when The time represents processing tasks at the UAS m server; representing that the task is not unloaded to the UAS m server for processing; When USE i offloads a computational task to BS j , the computational task is delayed in its transmission over the wireless channel Can be expressed as: computation delay required for executing tasks on BS j server Expressed as: Where f i,j denotes the computing resources allocated to the task by BS j ; thus, when a task is offloaded onto the BS j server, the execution latency of the task can be expressed by the formula: Wherein, the Representing binary decisions when When the BS j server processes the task Time means that tasks are not processed on the BS j server; To sum up, the total task execution latency of USE i can be expressed as: the optimization objective is to minimize the execution delay of the task under the following constraints; unloading decision constraint that tasks of all user equipment can only select one unloading mode; Unloading decision and value constraint, namely unloading decision of the edge server of each network area to the user task is a Boolean variable, and only a value of 0 or 1 can be obtained; The execution time delay constraint is that the task execution time delay cannot exceed the maximum completion time delay acceptable by the user equipment for the task; Computing resource allocation constraints-the computing resources allocated to user tasks by STS, UAS and BS edge servers cannot exceed the maximum allocatable computing resources of the edge servers, namely: Wherein, the Representing the maximum computing resource allocation capability of the STS; representing a maximum computing resource allocation capability of the UAS; Representing the maximum computing resource allocation capability of the BS; the objective function of the optimization problem can be expressed in particular as:
4. 4. The device for establishing the evolution game-based 6G space-time integrated network resource allocation according to claim 1, wherein the step 3) adopts a combined task unloading and resource allocation algorithm to solve the task unloading and resource allocation problems, and the algorithm steps are as follows: (1) Initializing the number of satellites, unmanned aerial vehicles, base stations and user equipment and a resource allocation result; (2) Calculating task transmission rates of different channels according to parameters such as channel bandwidth, gain, path loss index and the like; (3) Solving an optimal unloading decision by using a particle swarm task unloading optimization algorithm and a current optimal computing resource allocation scheme; (4) And solving an optimal computing resource allocation scheme by utilizing an evolutionary dynamic game computing resource allocation algorithm and a current optimal unloading decision.

Description

6G space-world integrated network resource allocation device based on evolution game Technical Field The invention relates to a communication technology, in particular discloses a 6G space-earth integrated network resource allocation device based on an evolution game, and belongs to the technical field of calculation, calculation or counting. Background Future 6G mobile communication will build Space-Air-Ground integrated network, SAGIN integrated network communication system, which combines the advantages of Space, air and ground infrastructures, further satisfies the demands of various users for communication anytime and anywhere, and achieves the ubiquitous coverage goal of mobile communication networks. In addition, an air-to-ground integrated network will promote the development of emerging applications such as internet of things (IoT), internet of vehicles (IoV), industrial internet, and the like. Therefore, the space-world integrated network greatly changes the life of people, and has important practical significance for researching the space-world integrated network. However, the size and the required calculation amount of the task initiated by the ground user equipment are different, so that the time delay of the task is different. Because the computing resources of the edge server are limited, the problem of unbalanced resource allocation may occur, some devices may overload resources due to excessive tasks, and other devices idle resources due to insufficient tasks, so that the overall resource utilization rate is reduced, and the efficiency and performance of the system are affected. Furthermore, when multiple tasks are offloaded simultaneously to the same device for processing, exceeding their processing capabilities can result in increased latency. Aggravating resource contention may also conflict between tasks, potentially rendering some computationally intensive tasks unable to be handled in time. Thus, it is a great challenge to offload the different types of tasks generated by the user equipment to the satellite edge server, the drone edge server, or the base station edge server for processing to minimize latency. Disclosure of Invention The invention designs a 6G space-earth integrated network resource allocation device based on evolution game aiming at the problems that a plurality of tasks compete for limited computing resources at the same time, so that resource allocation is unbalanced, task processing time delay is increased and the like. Firstly, a 6G space-earth integrated calculation unloading network model is constructed. Secondly, an optimization objective and constraints are defined to minimize task execution latency. And finally, solving the task unloading and resource allocation problems by adopting a combined task unloading and resource allocation algorithm. The invention discloses a 6G space-earth integrated network resource allocation device based on evolution game, which comprises the following three steps: 1) Constructing a 6G space-earth integrated computing offload network model, wherein the network model comprises three layers of networks, namely a space-earth network, a space-earth network and a foundation network, wherein the space-earth network comprises N LEO satellites with edge servers configured in the space-earth network and is recorded as STS, the STS set can be represented as STS= { STS 1,STS2,...,STSn,...,STSN|n∈N},STSn and represents an N-th LEO satellite, the communication range of the STS set covers the whole foundation network and can be communicated with user equipment and process computing tasks unloaded by the user equipment, the space-earth network comprises M Unmanned Aerial Vehicles (UAVs), a communication module and an edge server are configured on the UAV and are recorded as UAS, the UAS set can be represented as UAS= { UAS 1,UAS2,...,UASm,...,UASM|m∈M},UASm and represents an M UAV, the effective communication radius of the UAS is recorded as r UAS and can provide communication/computing services for the user equipment, the foundation network comprises I user equipment (USE) and J Base Stations (BS), each of which is provided with edge servers, wherein the USE set can be recorded as USE= { 34E24|E epsilon, and BS 35 and the effective radius of the BS is recorded as 35; In this network model, only USE will spontaneously generate computational tasks, STS, BS and UAS can only perform tasks but will not spontaneously generate computational tasks, USE i in each time slot generates a computational task to be processed, the task can be represented by a triplet < D i,Ci,Timax >, D i represents the task data size, C i represents the task calculation, i.e. the computational resources required for completing the task, T imax represents the maximum acceptable task completion time, USE i can offload tasks to edge servers of each network area for processing, USE i can offload tasks to STS for execution in the sky base area through USE-STS communication links,