边缘计算环境下的多任务多边缘分配

Shihao Li, Weiwei Miao, Zeng Zeng, Lei Wei, Chengling Jiang, Chuanjun Wang, Mingxuan Zhang
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引用次数: 0

摘要

随着物联网(IoT)和社交网络应用的快速发展,云正在向网络边缘移动。可以预见,越来越多的数据将在边缘处理,研究机构估计超过90%的数据将在本地存储和处理。本文主要研究多作业多边缘环境下的资源分配问题。我们将分配问题表述为并发作业调度问题(CJSP),该问题被证明是np完全的。针对CJSP的一种特殊情况,提出了权重平衡算法,并证明了权重平衡算法在某些条件下是最优的。然后我们扩展WB来解决一般的CJSP。大量的仿真表明,该算法在小用户和边缘规模下的性能几乎与最优算法一样好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Job Multi-Edge Allocation in Edge Computing Environments
With the rapid advancement of Internet of Things (IoT) and social networking application, the clouds is moving towards the network edges. It is foreseeable that more and more data will be processed in edge, and research organizations estimate that over 90% of the data will be stored and processed locally. This paper focus on the resource allocation for the multi-job multi-edge environments. We formulate the allocation problem as the concurrent job scheduling problem (CJSP), which is shown to be NP-complete. We propose the Weight Balance (WB) Algorithm to solve a special case of CJSP and we show that WB is optimal under some conditions. We then expand WB to solve the general CJSP. Extensive simulations demonstrate that the performance of our algorithm at small user and edge scale is almost as good as the optimal algorithm.
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