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D2D-Enabled Mobile-Edge Computation Offloading for Multiuser IoT Network

机译:用于多用户IOT网络的D2D的移动边缘计算卸载

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摘要

The emerging mobile-edge computing paradigm provides opportunities for the resource-hungry mobile devices (MDs) to migrate computation. In order to satisfy the requirements of MDs in terms of latency and energy consumption, recent researches proposed diverse computation offloading schemes. However, they either fail to consider the potential computing resources at the edge, or ignore the selfish behavior of users and the dynamic resource adaptability. To this end, we study the computation offloading problem and take into consideration the dynamic available resource of idle devices and the selfish behavior of users. Furthermore, we propose a game theoretic offloading method by regarding the computation offloading process as a resource contention game, which minimizes the individual task execution cost and the system overhead. Utilizing the potential game, we prove the existence of Nash equilibrium (NE), and give a lightweight algorithm to help the game reach a NE, wherein each user can find an optimal offloading strategy based on three contention principles. Additionally, we conduct analysis of computational complexity and the Price of Anarchy (PoA), and deploy three baseline methods to compare with our proposed scheme. Numerical results illustrate that our scheme can provide high-quality services to users, and also demonstrate the effectiveness, scalability and dynamic resource adaptability of our proposed algorithm in a multiuser network.
机译:新出现的移动边缘计算范例为迁移计算的资源饥饿的移动设备(MDS)提供了机会。为了满足延迟和能耗方面的MDS的要求,最近的研究提出了各种计算卸载方案。但是,它们要么无法考虑边缘处的潜在计算资源,或忽略用户的自私行为和动态资源适应性。为此,我们研究了计算卸载问题,并考虑了空闲设备的动态可用资源和用户的自私行为。此外,我们通过将游戏理论上的摘机方法提出了一种作为资源争用游戏的计算卸载过程,其最小化各个任务执行成本和系统开销。利用潜在的游戏,我们证明了纳什均衡(NE)的存在,并提供了一种轻量级算法来帮助游戏到达NE,其中每个用户可以基于三个竞争原理找到最佳的卸载策略。此外,我们对计算复杂性和无政府状态价格进行分析,并部署三种基线方法以与我们提出的计划进行比较。数值结果说明我们的方案可以向用户提供高质量的服务,并还展示了我们在多用户网络中所提出的算法的有效性,可扩展性和动态资源适应性。

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