Energy Efficient Mobile Edge Computing using Joint Benders Decomposition and Distributed Dinkelbach Algorithm

Currently, executing computation intensive and time sensitive tasks among the network becomes a significant challenge. Traditional cloud computing executes the task with high latency and energy cost. Mobile edge computing (MEC) is proposed as a supplement to cloud computing. In this paper, we formulate a problem to minimize the energy cost in MEC, considering transmit power and latency constraints. To solve the proposed mixed integer nonlinear programming problem, we propose a joint Benders decomposition and distributed Dinkel-bach algorithm. The Benders decomposition performs as an outer loop algorithm, which separates the original problem into the subproblem and master problem. The distributed Dinkelbach algorithm solves subproblem in the inner loop in a distributed manner. The simulation results show that our proposed algorithm is energy efficient with high reliability.