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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing
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Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing

机译：基于Cloudlet的移动边缘计算中IoT传感器的能源感知计算分流

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摘要

Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.
机译：提议将移动边缘计算作为一种有前途的计算范例，以减轻数据中心和移动网络的过多负担，这是由物联网（IoT）的快速增长引起的。这项工作介绍了云辅助的多cloudlet框架，以在基于cloudlet的移动边缘计算中提供可伸缩服务。由于小云的计算资源有限，而无线接入点（AP）的通信资源有限，因此具有相同计算卸载决策的IoT传感器彼此交互。为了优化计算任务的处理时延和能耗，本文对物联网传感器的计算卸载决策问题进行了理论分析。更详细地，将物联网传感器的计算卸载决策问题表述为计算卸载博弈，并通过引入潜在博弈工具推导纳什均衡的条件。通过利用游戏的有限改进属性，计算卸载决策（COD）算法旨在为IoT传感器提供分散的计算卸载策略。仿真结果表明，与随机选择算法和云优先算法相比，COD算法可以显着降低系统成本。此外，COD算法可以随着物联网传感器的增加而很好地扩展。

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