Peer-to-Peer Enhanced Task Scheduling for D2D Enabled MEC Network
Zhigang Xie, Xin Song, Siyang Xu
Abstract
The low computational capacity of mobile devices has become the main performance bottleneck for emerging computing-intensive and delay-sensitive applications. In this paper, we propose a peer-to-peer (P2P) enhanced task scheduling framework to minimize the average task duration in device-to-device (D2D) enabled mobile edge computing (MEC) network by jointly optimizing the task scheduling decision and the computational resource allocation. Our proposed framework can work in different modes in different application scenarios. In the MEC mode, an iterative algorithm is presented based on alternating optimization technology and sorting algorithm, which can derive a near-optimal solution of the original mixed-integer non-linear programming (MINLP) optimization problem. In the P2P mode, we can reformulate the original problem to a typical one-to-one assignment problem, which is solved by a task scheduling algorithm based on the Hungarian method. In more challenging hybrid mode, we make some simplifications based on reformulation linearization technology. Then, the near-optimal solution is obtained by our proposed scheduling algorithm based on the alternating direction method of multipliers (ADMM) method and difference of convex functions (D.C.) programming. Numerical results show that our proposed framework has shorter average task duration under different scheduling modes compared with the other scheduling schemes.