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Task Offloading and Resource Allocation in Heterogeneous Edge Computing Systems

机译：异构边缘计算系统中的任务卸载和资源分配

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摘要

The computing architecture undergoes a trend toward heterogeneity, which introduces a new challenge of task offloading scheduling in multi-server mobile edge computing system. Considering the inherent heterogeneity of task parallelism, this paper investigates the interesting problem of how to exploit the parallelism of task and server by reasonably scheduling task offloading. We jointly optimize task offloading decision and resource allocation so as to minimize system-wide computation overhead in terms of task completion time and energy consumption. Leveraging the structure of the formulated problem, we decompose the original problem into task offloading decision problem and resource allocation problem. To solve for task offloading decision, we propose a heuristic algorithm based on the designed user preference, while we address resource allocation problem by quasiconvex and convex optimization techniques. Simulation results demonstrate that our proposed algorithm outperforms the existed benchmark approach, and that prominent gains can be achieved by conditionally deploying heterogeneous server.
机译：计算架构经历了异质性的趋势，这引入了多服务器移动边缘计算系统中的任务卸载调度的新挑战。考虑到任务并行性的固有异质性，本文通过合理调度任务卸载来调查如何利用任务和服务器的并行性的有趣问题。我们共同优化任务卸载决策和资源分配，以便在任务完成时间和能量消耗方面最小化系统范围的计算开销。利用制定问题的结构，我们将原始问题分解为任务卸载决策问题和资源分配问题。为了解决任务卸载决策，我们提出了一种基于设计的用户偏好的启发式算法，而我们通过准iconvex和凸优化技术解决了资源分配问题。仿真结果表明，我们所提出的算法优于存在的基准方法，并且通过有条件地部署异构服务器，可以实现突出的增益。

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