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Decentralized Continuous Game for Task Offloading in UAV Cloud

机译:无人机云中用于任务卸载的分散式连续游戏

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UAV cloud which integrates the flexibility and re-silience of mobile cloud computing (MCC) with multiple UAV system provides drones the ability of processing compute-intensive application by offloading task to cloud. However, such task with heterogeneous quality of experience (QoE) requirement generated by massive drones becomes a troublesome burden for cloud resource allocation. Especially the endurance issue related to the energy efficiency makes the problem more complicated. This paper proposes a game theory based decentralized continuous offloading algorithm. Each drone in the UAV cloud optimizes the percentage of offloading task executed at cloud, while minimizes its overhead composed by QoE requirement and energy consumption. This algorithm can be proved to a potential game that can reach a bilateral satisfaction Nash Equilibrium (NE) by finite iteration. Numerical results under various scenario corroborate not only the effectiveness and stability of the proposed continuous offloading game, but also the superiority of computation complexity and communication overhead.
机译:UAV云将移动云计算(MCC)的灵活性和灵活性与多个UAV系统集成在一起,使无人机能够通过将任务卸载到云来处理计算密集型应用程序。但是,这种由大型无人机生成的具有异质体验质量(QoE)要求的任务成为云资源分配的麻烦负担。特别是与能源效率有关的耐久性问题使问题更加复杂。本文提出了一种基于博弈论的分散连续卸载算法。 UAV云中的每架无人机都可以优化在云上执行的卸载任务的百分比,同时将其QoE需求和能耗所造成的开销降至最低。可以证明该算法适用于通过有限迭代达到双边满意纳什均衡(NE)的潜在博弈。在各种情况下的数值结果不仅证实了所提出的连续卸载游戏的有效性和稳定性,而且证实了计算复杂性和通信开销的优越性。

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