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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.

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