Abstract: Relay-assisted mobile edge computing(MEC) has recently emerged as a promising paradigm to enhance resource utilization and data processing capability of low-power networks,such as 5G networks and Internet of things (IoT).Nevertheless,the design of relay selection and computation offloading policies to improve the energy efficiency for queue stability system remains challenging.In order to solve the energy consumption optimization problem in relay-assisted MEC system,a mixed integer nonli-near stochastic optimization model is established,with the objective of minimizing the long-term average energy consumption,subject to a task buffer stability constraint.The problem is solved by decomposing into two stages:relay selection and relay offloa-ding decision.In relay selection stage,the relay node is determined by setting a weighted parameter V₁ to minimize the weighted sum of transmission energy consumption and buffer queue length.In offloading decision stage,the stochastic optimization is converted to a deterministic optimization problem based on Lyapunov optimization method.Specifically,at each time slot,the theore-tical expressions of optimal relay calculation frequency,relay transmission power and remote calculation frequency are obtained under the constraint of task buffer queue stability.Simulation results show that the energy optimization strategy can effectively reduce the long-term average energy consumption under the constraint of buffer queue stability,and converge to the optimal solution obtained by exhaustive searching.Besides,the weight of energy consumption and waiting time can be changed by adjusting the values of parameters V₁ and V₂ in algorithm.

Key words: Mobile edge computing, Relay selection, Buffer queue, Offloading decision, Energy optimization