  Driven by explosive computation demands of Internet of Things (IoT), mobile
edge computing (MEC) provides a promising technique to enhance the computation
capability for mobile users. In this paper, we propose a joint resource
allocation and load management mechanism in an MEC system with wireless power
transfer (WPT), by jointly optimizing the transmit power for WPT, the
local/edge computing load, the offloading time, and the frequencies of the
central processing units (CPUs) at the access point (AP) and the users. To
achieve an energy-efficient and sustainable WPT-MEC system, we minimize the
total energy consumption of the AP, while meeting computation latency
requirements. Cooling energy which is non-negligible, is taken into account in
minimizing the energy consumption of the MEC system. By rigorously
orchestrating the state-of-the-art optimization techniques, we design an
iterative 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.
