Green resource allocation for mobile edge computing

• DOI: 10.1016/j.dcan.2022.03.001
• Publication Date: 2022-03-10T02:27:08Z
• Authors: Anqi Meng; Guandong Wei; Yao Zhao; Xiaozheng Gao; Zhanxin Yang
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; Mobile edge computing; Green communications; Mixed-integer programming; Information technology; 02 engineering and technology; Resource allocation; T58.5-58.64

We investigate the green resource allocation to minimize the energy consumption of the users in mobile edge computing systems, where task offloading decisions, transmit power, and computation resource allocation are jointly optimized. The considered energy consumption minimization problem is a non-convex mixed-integer non-linear programming problem, which is challenging to solve. Therefore, we develop a joint search and Successive Convex Approximation (SCA) scheme to optimize the non-integer variables and integer variables in the inner loop and outer loop, respectively. Specifically, in the inner loop, we solve the optimization problem with fixed task offloading decisions. Due to the non-convex objective function and constraints, this optimization problem is still non-convex, and thus we employ the SCA method to obtain a solution satisfying the Karush-Kuhn-Tucker conditions. In the outer loop, we optimize the offloading decisions through exhaustive search. However, the computational complexity of the exhaustive search method is greatly high. To reduce the complexity, a heuristic scheme is proposed to obtain a sub-optimal solution. Simulation results demonstrate the effectiveness of the developed schemes.