JOAGT: Latency-Oriented Joint Optimization of Computation Offloading and Resource Allocation in D2D-Assisted MEC System
Xue Wang, Yingbin Han, Haotian Shi, Zhihong Qian
Abstract
Driven by the visions of Internet of Things and 5G communications, mobile edge computing (MEC) as a new paradigm promises dramatic reduction in latency. In recent years, an increasing number of scholars introduce D2D communication into the MEC system to further reduce the latency. In this letter, we propose a D2D-enabled MEC three-layer partial offloading scenario and design a joint optimization algorithm based on game theory (JOAGT). The proposed algorithm includes offloading mode selection, offloading fraction allocation, and resource allocation. Simulation results show that the proposed scenario and algorithm can significantly reduce the total latency, and the algorithm can exhibit good performance.