Research On Task Offloading And Base Station Dormancy Strategy In Mobile Edge Computing

Mobile Edge Computing(MEC),as the core technology of 5G,significantly reduces data transmission delays and controls network congestion by providing IT services and computing resources at the edge of mobile networks.With the increasing computing demands of new applications,it is increasingly important to design a reasonable task offload strategy for multiuser multi-server MEC systems and provide excellent service quality.Because mobile devices are often limited by their own power,the execution and transmission of computing tasks will be interrupted,resulting in a poor user experience.Energy Harvesting(EH)technology was introduced to alleviate the contradiction between high energy consumption of computing tasks and limited battery capacity of mobile devices.In a MEC system with multiple users and multiple servers and users with mobility,it is particularly important to study low-latency and low-energy computing offloading strategies to solve the problem of computing resource competition.First of all,this article aims at the trade-off between task execution delay and energy consumption,and builds an optimization model of execution cost.Lyapunov optimization method is used to solve the best energy collection and the best calculation mode selection under a single device.Secondly,to solve the problem of MEC server computing resource competition,the concept of network flow is introduced to design a user-server matching model.Considering the optimization of the average task execution cost of the entire system,a task offloading strategy based on minimum cost and maximum flow is proposed.Simulation results show that the offload strategy can quickly obtain the best match between the user and the server while ensuring a very low task drop rate.Compared with other benchmark methods such as greedy strategy,this strategy can achieve lower average task execution cost and higher task offloading ratio.Next,in view of the particularity of the IoT application scenario and the need to reduce energy consumption,this article builds a heterogeneous cellular network with a three-layer structure.Utilizing the difference of base station transmit power in heterogeneous cellular networks to meet different data traffic requirements in various regions.In order to cope with the complexity and energy efficiency of heterogeneous networks,this article proposes a joint optimization algorithm based on maximizing energy efficiency for user access and base station and MEC server sleep.This algorithm solves the problem of load balancing in heterogeneous networks,effectively saves the energy cost of the base station during the task offloading process,and maximizes the overall energy efficiency of the network.Finally,simulation results prove the effectiveness of the proposed method.