An Enhanced PROMOT Algorithm with D2D and Robust for Mobile Edge Computing
Jin Wang, Wenbing Wu, Zhuofan Liao, Yeon-Woong Jung, Jeong‐Uk Kim
Abstract
With the development of the fifth-generation network (5G), the base station is becoming denser and denser, which leads to the user device is covered by multiple edge servers in mobile edge computing. Based on this, user devices have more options to decide on which server to offload the tasks. However, there may be still a few user devices located on the edge of a region that is not covered by any edge servers. The user device can only execute tasks locally resulting in excessive latency or energy consumption. To solve the problem, in this paper, an Enhanced PRiori Offloading Mechanism with joint Offloading proportion and Transmission (EPROMOT) power algorithm is proposed. Firstly, a mobile edge computing (MEC) model with device-to-device (D2D) technology is proposed. Then a tradeoff problem consists of the overhead of latency and energy consumption is formulated. Next, a Genetic algorithm is adopted to resolve the tradeoff problem. Besides a prevention mechanism is proposed to increase the robust when the edge server is shut down during the offloading time slot. Finally, experiments have performed to show the outperformance of the EPROMOT algorithm.