Stochastic computation resource allocation for mobile edge computing powered by wireless energy transfer

Limited battery capacity and poor computing capability of wireless devices have been longstanding performance limitations in the Internet of Things (IoT) era. Employing Wireless Energy Transfer (WET) technology, wireless devices of the Mobile Edge Computing (MEC) systems can be released from these limitations and achieve a better quality of experience (QoE). This paper considered a wireless powered mobile edge computing (WP-MEC) system with one mobile device, where a double antenna hybrid access point (HAP) (integrated with a MEC server) transmits wireless energy to the device and communicates with the wireless terminal to assist in its data processing. We investigated the average computation rate maximization problem in this system and proposed an online service rate maximization (OSRM) algorithm to tackle this problem. In each time slot, the proposed algorithm optimally decides the time allocation policy and the CPU-frequency for the mobile device. Simulation results show that the proposed algorithm can balance the time average computation rate and the task buffer queue length, and outperforms the benchmark schemes. (C) 2019 Elsevier B.V. All rights reserved.