Research On Computing Migration Based On Task Dependencies In The Mobile Cloud Computing Environment

With the development of intelligent mobile terminal technology,there are more and more mobile application software with complex functions.However,the improvement of hardware performance of mobile terminals lags behind the development of intelligent applications,and resource limitation issues are increasingly prominent.To this end,many scholars are committed to the migration of some computing tasks from the local to the cloud in the mobile cloud computing environment to achieve resource expansion of mobile terminals.However,compared with remote clouds,some complex applications with higher real-time requirements are more suitable for migration to micro-clouds.The dependencies between tasks in such applications will also have a greater impact on the migration scheme.And there is not much research on this issue.Based on the dependence between tasks and the characteristics of micro-clouds,this paper proposes a computational migration method based on the idea of genetic algorithm.According to the ability of different micro-clouds to handle different types of tasks,the micro-clouds are classified into types.According to the dual dependence of timing and data between different tasks in mobile applications,combined with energy consumption and response time considerations,a computational migration algorithm is designed to obtain a migration scheme with better utility values.Then,considering the application scenario of multiple mobile terminals with multiple micro-clouds,in this scenario,when a large number of computing tasks are migrated to the same micro-cloud,the overall response time is increased.In order to balance the load between micro-clouds,this paper designs a load balancing algorithm to minimize the overall response time.Finally,the feasibility and effectiveness of the two methods are verified by simulation.