低轨道卫星-地面边缘计算系统分布式计算卸载的博弈论方法

IF 7.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ying Chen;Yaozong Yang;Jintao Hu;Yuan Wu;Jiwei Huang
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引用次数: 0

摘要

由于计算资源和电池容量的限制,可以将地面设备的计算任务卸载到边缘服务器进行处理。此外,随着近地轨道卫星技术的发展,与传统的地面边缘计算网络相比,近地轨道卫星-地面边缘计算可以实现全球覆盖网络,提供超越区域限制的无缝计算服务。本文研究了低轨道卫星-地面边缘计算系统中的计算卸载问题。地面设备可以将其计算任务卸载到部署在边缘服务器上的地面基站(BSs)或LEO卫星上进行远程处理。在满足资源和低轨卫星通信时间约束的前提下,提出了设备成本最小化的计算卸载问题。由于每个地面设备都在竞争传输资源和计算资源以降低自己的卸载成本,我们将这个问题重新表述为LEO卫星-地面计算卸载博弈(LSTCO-Game)。推导出设备间的传输干扰和计算资源竞争存在上界。然后,从理论上证明了lstco -博弈中存在至少一个纳什均衡卸载策略。我们提出了博弈论的分布式计算卸载(GDCO)算法来寻找网元的卸载策略。其次,我们分析了在最坏情况下GDCO的NE卸载策略所获得的成本。将本文提出的GDCO算法与其他计算卸载方法进行了对比实验。结果表明,GDCO算法可以有效地降低卸载成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Game-Theoretical Approach for Distributed Computation Offloading in LEO Satellite-Terrestrial Edge Computing Systems
Due to the limitations of computing resources and battery capacity, the computation tasks of ground devices can be offloaded to edge servers for processing. Moreover, with the development of the low earth orbit (LEO) satellite technology, LEO satellite-terrestrial edge computing can realize a global coverage network to provide seamless computing services beyond the regional restrictions compared to the conventional terrestrial edge computing networks. In this paper, we study the computation offloading problem in the LEO satellite-terrestrial edge computing systems. Ground devices can offload their computation tasks to terrestrial base stations (BSs) or LEO satellites deployed on edge servers for remote processing. We formulate the computation offloading problem to minimize the cost of devices while satisfying resource and LEO satellite communication time constraints. Since each ground device competes for transmission and computing resources to reduce its own offloading cost, we reformulate this problem as the LEO satellite-terrestrial computation offloading game (LSTCO-Game). It is derived that there is an upper bound on transmission interference and computing resource competition among devices. Then, we theoretically prove that at least one Nash equilibrium (NE) offloading strategy exists in the LSTCO-Game. We propose the game-theoretical distributed computation offloading (GDCO) algorithm to find the NE offloading strategy. Next, we analyze the cost obtained by GDCO's NE offloading strategy in the worst case. Experiments are conducted by comparing the proposed GDCO algorithm with other computation offloading methods. The results show that the GDCO algorithm can effectively reduce the offloading cost.
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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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