Joint Optimization of Task Offloading and Resource Allocation in Mobile Edge Computing System

Traditional cloud computing usually does not meet the user needs for latency-sensitive applications, while mobile edge computing (MEC) reduces the pressure on the core network by sinking the computing power of the central cloud to the edge server close to the userTask offloading and resource allocation issues in MEC systems for multi-user, multi-servers. This article first uses the Lyapunov optimization technique to reconstruct the stochastic optimization problem.then uses the genetic algorithm to formulate the unloading decision, and finally uses the binary search method and the Lagrangian multiplier method to obtain the optimal solution of power allocation and computational resource allocation respectively. Through experimental simulation, the scheme adopted in this paper can reduce the cost and improve the system performance while keeping the system stable.