Joint Task Offloading and Resource Allocation Strategy for Hybrid MEC-Enabled LEO Satellite Networks: A Hierarchical Game Approach

IF 8.3 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Communications Pub Date : 2024-10-10 DOI:10.1109/TCOMM.2024.3478111
Peixuan Li;Yichen Wang;Zhangnan Wang;Tao Wang;Julian Cheng
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Abstract

The multi-access edge computing (MEC)-enabled low Earth orbit (LEO) satellite network is a promising approach to meet the growing ubiquitous diverse computation demands around the world. In this paper, a joint task offloading and resource allocation strategy is proposed for hybrid MEC-enabled LEO satellite networks, where two types of MEC tasks, namely delay-sensitive edgy-cloud task and data-and computation-intensive cloudy-edge task, are considered simultaneously. Specifically, we first design the cost functions for the two types of tasks, which take the delay-sensitive feature of edgy-cloud task and data-and computation-intensive characteristics of cloudy-edge task into consideration. Then, an overall terminal cost minimization problem is formulated for task offloading and resource allocation under the communication and computation capability constraints and the service delay requirements. In practice, terminals usually only care about their own costs, but satellites pursue the overall cost minimization of all the served terminals. Thus, considering the individual and collective rationality simultaneously, a two-level hierarchical game is constructed to solve the formulated problem. In the upper level, a hedonic coalition formation game is established, which enables each terminal to make the coalition selection and task offloading decision based on the designed coalition switch rule. In the lower level, the joint channel and power allocation in each coalition is first formulated as a noncooperative game to represent the individual rationality of each terminal. Then, each satellite performs the optimal computation resource allocation to maximize the coalition value with collective rationality. We prove that the Nash equilibrium (NE) for the noncooperative game exists and the coalition partition converges to a Nash stable state. Simulation results are provided to demonstrate the superiority of the proposed strategy.
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混合 MEC-Enabled LEO 卫星网络的联合任务卸载和资源分配策略:分层博弈方法
基于多址边缘计算(MEC)的低地球轨道(LEO)卫星网络是满足全球日益增长的无处不在的多样化计算需求的一种有前途的方法。本文提出了一种基于混合MEC的LEO卫星网络联合任务卸载和资源分配策略,该策略同时考虑了延迟敏感型边缘云任务和数据计算密集型云边缘任务两种MEC任务类型。具体来说,我们首先设计了两类任务的代价函数,分别考虑了边缘云任务的延迟敏感特性和云边缘任务的数据和计算密集型特性。然后,在通信和计算能力约束和业务延迟要求下,提出了一个整体终端成本最小化问题,用于任务卸载和资源分配。在实践中,终端通常只关心自己的成本,而卫星则追求所有服务终端的总成本最小化。因此,同时考虑个人和集体的理性,构建了一个两级层次博弈来解决公式化问题。上层建立享乐联盟形成博弈,使各终端根据设计的联盟切换规则进行联盟选择和任务卸载决策。在较低层次上,首先将各联盟的联合通道和权力分配表述为非合作博弈,代表各终端的个体理性。然后,各卫星进行最优计算资源分配,使联盟价值具有集体理性最大化。证明了非合作对策的纳什均衡存在,联盟划分收敛于纳什稳定状态。仿真结果证明了该策略的优越性。
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来源期刊
IEEE Transactions on Communications
IEEE Transactions on Communications 工程技术-电信学
CiteScore
16.10
自引率
8.40%
发文量
528
审稿时长
4.1 months
期刊介绍: The IEEE Transactions on Communications is dedicated to publishing high-quality manuscripts that showcase advancements in the state-of-the-art of telecommunications. Our scope encompasses all aspects of telecommunications, including telephone, telegraphy, facsimile, and television, facilitated by electromagnetic propagation methods such as radio, wire, aerial, underground, coaxial, and submarine cables, as well as waveguides, communication satellites, and lasers. We cover telecommunications in various settings, including marine, aeronautical, space, and fixed station services, addressing topics such as repeaters, radio relaying, signal storage, regeneration, error detection and correction, multiplexing, carrier techniques, communication switching systems, data communications, and communication theory. Join us in advancing the field of telecommunications through groundbreaking research and innovation.
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