Abstract:

Mobile edge computing can reduce the task computing delay and energy consumption of mobile terminals by sinking computing resources and storage resources to the edge of the mobile network,so as to effectively meet the requirements of high return bandwidth and low delay required by the rapid development of the mobile Internet and Internet of things.As a major advantage of mobile edge computing,the computing offload improves the mobile service capability by migrating heavy computing tasks to the edge server.In this paper,a task offloading solutions to minimize system response delay and mobile terminal energy consumption is proposed for mobile terminal applications with low latency and low energy consumption in mobile edge computing scenarios.First,based on the comprehensive consideration of the delay and energy consumption of mobile terminal execution tasks,the task slicing model,time delay model,energy consumption model and target optimization model are constructed;second,an improved immune optimization algorithm and a task offloading solution based on immune optimization are proposed;finally,the proposed solutions are compared with the LOCAL Execution solutions and the offloading solutions based on the genetic algorithm.Simulation results show that the proposed scheme is better than the literature scheme in terms of the comprehensive cost of delay and energy consumption,and can meet the unloading requirements of mobile terminal applications with low delay and low energy consumption.

Key words: mobile edge computing, task offload, immune algorithm, task processing, offloading delay