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Job Scheduling to Minimize Total Completion Time on Multiple Edge Servers

机译:作业调度以最小化多个边缘服务器上的总完成时间

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摘要

The mobile devices can send jobs to be processed at one of the nearby edge servers rather than the remote cloud server with low latency in edge computing systems. One key problem in such environment is how to assign the jobs to the edge servers so that the completion time is minimized. In this article, we propose a general model for this problem by considering the arbitrary arriving time of the jobs, the different processing speeds of the edge servers, the different time for uploading a job to different edge servers and the delay for returning the result back to a mobile device. Our goal is to minimize the total response time for complete all the jobs. We study a series of instances for this problem and provide lower bounded approximated offline algorithms in edge computing environments. The approximation ratio of our algorithm for the general problem is (max{2 + s(max)/s(min), d(max)/d(min)}). And it can be easily transformed to online algorithm whose theoretical performance is no twice worse than the offline algorithm. Moreover, the algorithm can be easily implemented in distributed systems. Extensive simulations show that both the proposed offline and online algorithms can derive good performance comparing with the optimal solution.
机译:移动设备可以在附近的边缘服务器之一,而不是边缘计算系统中具有低延迟的远程云服务器发送要在附近的边缘服务器之一进行处理。这种环境中的一个关键问题是如何将作业分配给边缘服务器,以便完成完成时间。在本文中,我们通过考虑作业的任意到达时间,边缘服务器的不同处理速度,将作业上载到不同的边缘服务器的不同时间以及返回结果的延迟来提出一般模型。到移动设备。我们的目标是最大限度地减少完成所有工作的总响应时间。我们研究了一系列问题的实例,并在边缘计算环境中提供了下限的近似的离线算法。我们的常规问题算法的近似比是(最大{2 + s(max)/ s(min),d(max)/ d(min)})。它可以很容易地转换为在线算法,其理论性能与离线算法的两倍差。此外,该算法可以在分布式系统中容易地实现。广泛的模拟表明,建议的离线和在线算法都可以导出与最佳解决方案相比的良好性能。

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