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QoS-Aware Fog Resource Provisioning and Mobile Device Power Control in IoT Networks

机译:QoS感知雾资源配置和IOT网络中的移动设备功率控制

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Fog-aided Internet of Things (IoT) addresses the resource limitations of IoT devices in terms of computing and energy capacities, and enables computational intensive and delay sensitive tasks to be offloaded to the fog nodes attached to the IoT gateways. A fog node, utilizing the cloud technologies, can lease and release virtual machines (VMs) in an on-demand fashion. For the power-limited mobile IoT devices (e.g., wearable devices and smart phones), their quality of service may be degraded owing to the varying wireless channel conditions. Power control helps maintain the wireless transmission rate and hence the quality of service (QoS). The QoS (i.e., task completion time) is affected by both the fog processing and wireless transmission; it is thus important to jointly optimize fog resource provisioning (i.e., decisions on the number of VMs to rent) and power control. This paper addresses this joint optimization problem to minimize the system cost (VM rentals) while guaranteeing QoS requirements, formulated as a mixed integer nonlinear programming problem. An approximation algorithm is then proposed to solve the problem. Simulation results demonstrate the performance of our proposed algorithm.
机译:雾化物联网(物联网)在计算和能量容量方面地解决了物联网设备的资源限制,并使计算密集型和延迟敏感任务能够将其卸载到附加到物联网网关的雾节点。利用云技术的雾节点可以按需求方式租赁和释放虚拟机(VM)。对于电流限制移动物联网设备(例如,可穿戴设备和智能手机),由于无线频道条件不同,它们的服务质量可能会降低。电源控制有助于维护无线传输速率,从而保持服务质量(QoS)。 QoS(即任务完成时间)受雾处理和无线传输的影响;因此,重要的是共同优化雾资源供应(即,关于租用VM的数量)和电源控制的决定。本文解决了该联合优化问题,以最大限度地减少系统成本(VM租赁),同时保证QoS要求,配制为混合整数非线性规划问题。然后提出了一种近似算法来解决问题。仿真结果展示了我们所提出的算法的性能。

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