时变 HAP 和 LEO 卫星集成 MEC 网络中计算卸载和分割的效用优化

IF 4.4 2区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Ruidong Zhang, Jiadong Zhang, Xue Wang, Wenxiao Shi
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引用次数: 0

摘要

为了向偏远地区和灾区提供无处不在的低延迟通信和计算服务,高空平台(HAP)和低地球轨道(LEO)卫星集成多接入边缘计算(HLS-MEC)网络已成为一种前景广阔的解决方案。然而,目前的大多数研究都直接假定连接卫星的数量是固定的,而忽略了时变多卫星计算过程的建模。受此启发,我们建立了一个 M/G/K(t)队列模型来说明卫星上的任务计算。为了评估计算卸载和拆分的效率和质量,我们建立了一个效用模型。该模型被定义为评估任务卸载权衡的价值函数(考虑延迟减少和能源节约)与成本函数(量化与延迟和能源消耗相关的费用)之间的差值。在提出效用最大化问题后,我们提出了基于深度强化学习的卸载和拆分(DBOS)方案,该方案可以克服 HLS-MEC 网络中的时变不确定性和高动态性。具体来说,DBOS 方案可以通过感知连接卫星的数量、HAP 与卫星之间的距离、可用计算资源和任务到达率,学习最佳计算卸载和拆分策略,以实现效用最大化。最后,我们评估并验证了 DBOS 方案的计算复杂性和收敛性。数值结果表明,DBOS 方案优于其他三个基准方案,并能在时变动态条件下实现效用最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utility optimization for computation offloading and splitting in time-varying HAP and LEO satellite integrated MEC networks
To provide ubiquitous and low-latency communication and computation services for remote and disaster areas, high altitude platform (HAP) and low earth orbit (LEO) satellite integrated multi-access edge computing (HLS-MEC) networks have emerged as a promising solution. However, most current studies directly assume that the number of connected satellites is fixed and neglect the modeling of the time-varying multi-satellite computing process. Motivated by this, we establish an M/G/K(t) queuing model to illustrate task computation on satellites. To evaluate the efficiency and quality of computation offloading and splitting, we develop a utility model. This model is defined as a difference between a value function that assesses the trade-offs of task offloading, considering latency reductions and energy savings, and a cost function that quantifies expenses related to latency and energy consumption. After formulating the utility maximization problem, we propose the deep reinforcement learning-based offloading and splitting (DBOS) scheme that can overcome the time-varying uncertainties and high dynamics in the HLS-MEC network. Specifically, the DBOS scheme can learn the best computation offloading and splitting policy to maximize the utility by sensing the number of connected satellites, the distance between the HAP and satellites, the available computing resources, and the task arrival rate. Finally, we evaluate and validate the computational complexity and convergence property of the DBOS scheme. Numerical results show that the DBOS scheme outperforms the other three benchmarks and maximizes the utility under time-varying dynamics.
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来源期刊
Computer Networks
Computer Networks 工程技术-电信学
CiteScore
10.80
自引率
3.60%
发文量
434
审稿时长
8.6 months
期刊介绍: Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.
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