分布式微服务感知无线蜂窝网络的能耗最小化

Yue Shan, Qi Zhu, Yaru Fu
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引用次数: 0

摘要

本文的重点是通过解决分布式感知微服务无线蜂窝网络(DMS-WCNs)中联合微服务(MS)的放置和计算资源分配问题来最小化能耗。我们提出了一个范例,其中每个大型服务由分布在不同小型基站(SBSs)之间的几个轻量级MSs组成,以执行单个功能。对于任意的服务请求,宏基站(MBS)调用缓存了必要的MSs来执行相应的计算任务的SBSs。计算完成后,sbs将结果发送回MBS,然后MBS集成并将最终结果交付给用户。考虑到用户的服务延迟需求和SBSs有限的缓存和计算资源的实际考虑,我们制定了最小化问题。为了有效地解决这个问题,我们开发了一个两阶段的方法。在第一阶段,我们推导了计算资源分配策略的封闭表达式。在第二阶段,我们引入了面向交换的算法来探索改进的MS放置策略。仿真结果表明,与穷举算法相比,我们提出的算法达到了接近最优的性能,并且显著优于其他基准测试策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Consumption Minimization for Distributed Microservice-Aware Wireless Cellular Networks
This paper focuses on minimizing energy consumption by addressing the joint microservice (MS) placement and computing resource allocation problem in distributed MS-aware wireless cellular networks (DMS-WCNs). We propose a paradigm in which each large service is composed of several lightweight MSs distributed among different small base stations (SBSs) to perform individual functions. For an arbitrary service request, the macro base station (MBS) invokes the SBSs that have cached the necessary MSs to execute the corresponding computational tasks. Once the computation is completed, the SBSs send the results back to the MBS, which then integrates and delivers the final result to the user. Taking into account the practical considerations of users’ service latency requirements and SBSs’ limited caching and computing resources, we formulate the minimization problem. To solve it efficiently, we develop a two-stage approach. In the first stage, we derive the closed-form expression of the computing resource allocation policy with regard to the MS placement. In the second stage, we introduce the swapping-oriented algorithm to explore an improved MS placement strategy. The simulation results demonstrate that our proposed algorithm achieves close-to-optimal performance compared to the exhaustive algorithm and significantly outperforms the other benchmark strategies.
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