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Multi-Job Multi-Edge Allocation in Edge Computing Environments

机译:边缘计算环境中的多作业多边分配

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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.
机译:随着物联网(物联网)和社交网络应用的快速进步,云正在向网络边缘移动。 它是可预见的,越来越多的数据将在边缘处理,研究组织估计超过90%的数据将在本地存储和处理。 本文侧重于多作业多边环境的资源分配。 我们将分配问题作为并发作业调度问题(CJSP)制定,其显示为NP-Treatport。 我们提出了重量平衡(WB)算法来解决CJSP的特殊情况,我们表明WB在某些条件下最佳。 然后,我们将WB扩展以解决一般CJSP。 广泛的模拟表明,我们的算法在小用户和边缘比例下的性能几乎与最佳算法一样好。

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