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A Competitive Approximation Algorithm for Data Allocation Problem in Heterogenous Mobile Edge Computing

机译:异构移动边缘计算中数据分配问题的竞争近似算法

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摘要

In recent years, the fast development of mobile computing has substantially promoted the mobile edge computing (also known as multi-access edge computing, MEC). Placing content in edges is one of the most important uses of MEC for that it can benefit a variety of service and applications such as video streaming and VR/AR. Currently, most of the existing researches are application specified, and the heterogeneities in data allocating devices and content have not been sufficiently explored. Aiming at developing a general optimal data allocating decision algorithm for MEC, in this work, we carry out in-depth study on the interaction of data allocating and fetching in heterogenous edge computing networks, showing the NP-hardness of the optimal decision problem. We then present polynomial algorithms with (1 - 1/e)-approximation factor. Our algorithms has reasonable performance guarantee with low computation complexity. We verify the proposed approach with analysis and simulations.
机译:近年来,移动计算的快速发展极大地促进了移动边缘计算(也称为多路访问边缘计算,MEC)。将内容放在边缘是MEC的最重要用途之一,因为它可以使各种服务和应用程序受益,例如视频流和VR / AR。当前,大多数现有的研究是针对特定应用的,并且尚未充分探索数据分配设备和内容中的异质性。为了开发一种通用的MEC最优数据分配决策算法,本文对异构边缘计算网络中数据分配与获取的交互作用进行了深入研究,显示了最优决策问题的NP难点。然后,我们提出具有(1-1 / e)逼近因子的多项式算法。我们的算法具有合理的性能保证,并且计算复杂度较低。我们通过分析和仿真验证了提出的方法。

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