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Cooling-Aware Resource Allocation and Load Management for Mobile Edge Computing Systems

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Document pages: 28 pages

Abstract: Driven by explosive computation demands of Internet of Things (IoT), mobileedge computing (MEC) provides a promising technique to enhance the computationcapability for mobile users. In this paper, we propose a joint resourceallocation and load management mechanism in an MEC system with wireless powertransfer (WPT), by jointly optimizing the transmit power for WPT, thelocal edge computing load, the offloading time, and the frequencies of thecentral processing units (CPUs) at the access point (AP) and the users. Toachieve an energy-efficient and sustainable WPT-MEC system, we minimize thetotal energy consumption of the AP, while meeting computation latencyrequirements. Cooling energy which is non-negligible, is taken into account inminimizing the energy consumption of the MEC system. By rigorouslyorchestrating the state-of-the-art optimization techniques, we design aniterative algorithm and obtain the optimal solution in a semi-closed form.Based on the solution, interesting properties and insights are summarized.Extensive numerical tests show that the proposed algorithm can save up to 90.4 the energy of existing benchmarks.

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