空天地一体化边缘计算网络中基于博弈论的任务卸载策略

doi:10.19678/j.issn.1000-3428.0069161

摘要/Abstract

摘要：

受地理因素的影响, 在偏远地区无法大规模建设通信网络的基础设施, 导致这些地区的网络通信质量降低以及一系列时延敏感型任务得不到及时处理和响应。针对偏远地区网络覆盖范围有限的问题, 将空天地一体化网络(SAGIN)与移动边缘计算(MEC)相结合, 提出基于博弈论的任务卸载策略, 可为偏远地区用户的时延敏感型任务卸载提供低延迟和高可靠传输。考虑到SAGIN中卫星资源受限以及本地用户设备能量不足的特点, 首先, 提出一种卫星-无人机集群-地面的三层边缘计算网络架构, 在满足各地面任务的时延要求下, 将任务卸载问题转化为地面用户设备和边缘服务器之间的Stackelberg博弈, 并证明其是NP难的。此外, 利用势博弈证明了地面用户设备之间构成的非合作博弈存在纳什均衡(NE)。最后, 寻找任务的最优卸载策略来最小化系统卸载成本, 通过最优的卸载任务转发百分比策略来最大化边缘服务器的效用函数, 提出一种基于Stackelberg博弈的纳什均衡迭代卸载(NEIO-SG)算法。仿真实验结果表明, 与其他基线算法相比, NEIO-SG在任务卸载过程中的系统总时延减少约13%, 边缘服务器的能耗降低约35%。

关键词: 任务卸载, 空天地一体化网络, 移动边缘计算, Stackelberg博弈, 纳什均衡

Abstract:

Geographical factors often hinder the establishment of large-scale communication network infrastructure in remote areas, resulting in poor network quality and delays in processing sensitive tasks. A Space-Air-Ground Integrated Network (SAGIN) combined with Mobile Edge Computing (MEC) can address the limited coverage in these areas. The SAGIN-MEC system can provide low latency and highly reliable transmission for offloading delay-sensitive tasks for users in remote areas. Given the constrained satellite resources in the space-ground integrated network and the limited energy of local user equipment, this study first proposes a satellite-UAV cluster-ground three-layer edge computing network architecture. To address the delay requirements of various ground tasks, this study transforms the task offloading problem as a Stackelberg game between ground user equipment and edge servers, establishing that the problem is NP-hard. Additionally, using a potential game, the study proves the existence of a Nash Equilibrium (NE) in a non-cooperative game between ground user equipment. Finally, the study introduces a NE Iterative Offloading algorithm based on the Stackelberg Game (NEIO-SG). This algorithm aims to determine the optimal task offloading strategy that minimizes system offloading costs and the optimal forwarding percentage strategy that maximizes the utility function of the edge server. Simulation experimental results show that the NEIO-SG algorithm reduces total system latency during task offloading by approximately 13% and lowers the energy consumption of the edge server by approximately 35% compared with other baseline algorithms.

Key words: task offloading, Space-Air-Ground Integrated Network(SAGIN), Mobile Edge Computing(MEC), Stackelberg game theory, Nash Equilibrium(NE)

刘亮, 毛武平, 李汶蔚, 谭思源, 荆腾祥. 空天地一体化边缘计算网络中基于博弈论的任务卸载策略[J]. 计算机工程, 2025, 51(2): 238-249.

LIU Liang, MAO Wuping, LI Wenwei, TAN Siyuan, JING Tengxiang. Task Offloading Strategy Based on Game Theory in the Space-Air-Ground Integrated Edge Computing Networks[J]. Computer Engineering, 2025, 51(2): 238-249.

https://www.ecice06.com/CN/Y2025/V51/I2/238

图/表 9

图1 空天地一体化的边缘计算网络架构

Fig.1 Architecture of space-air-ground integrated edge computing network

图2 低轨卫星与地面用户在空间几何方面的关系示意图

Fig.2 Schematic diagram of the relationship between low Earth orbit satellites and ground users in terms of spatial geometry

图3 不同任务数的系统卸载成本

Fig.3 The offloading cost of system for different number of tasks

图4 在不同任务数量下的系统总延迟

Fig.4 The total delay of the system under different number of tasks

图5 在不同任务数量下边缘服务器的能耗

Fig.5 Energy consumption of edge servers under different number of tasks

图6 纳什均衡卸载算法的收敛性能

Fig.6 Convergence performance of Nash equilibrium offloading algorithm

图7 在不同任务数据量下的系统卸载成本

Fig.7 The offloading cost of the system under different data size of task

图8 任务在不同所需CPU周期下的系统卸载成本

Fig.8 The system offloading cost of task under different CPU cycles requirement

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