Research On Computing Task Offloading Strategy Based On Hierachical Mechanism

Long-distance transmission is projected to increase latency and energy consumption,and even impair the execution of computing operations,as mobile communication technology evolves and the range of Io T business applications grows.It is critical to provide innovative cloud computing solutions to meet the stringent latency and energy consumption requirements of corporate applications.Mobile Edge Computing(MEC)is a cloud computing service that is deployed to the mobile network’s edge,offering a hardware platform for the efficient execution of computing activities by terminal devices.However,the gap between the present limited energy resources of terminal equipment and the high energy consumption demands of developing artificial intelligence applications is becoming more apparent.Meanwhile,load imbalance may be produced by an uneven distribution of computing demand across edge servers once a high number of terminal devices offload tasks to edge servers.To that purpose,this thesis research the energy consumption of terminal equipment as well as edge server load balancing.The following are the specific contents:1.The MEC deployment scheme,typical application scenarios,task offloading,and load balancing algorithm are all investigated.Furthermore,a task offloading architecture based on a hierarchical mechanism is proposed for edge computing.2.A computing task offloading approach for terminal equipment based on comprehensive value is provided to address the problem of low comprehensive performance of terminal equipment due to restricted power that cannot meet business application requirements.The strategy aims to reduce terminal equipment energy consumption by calculating the comprehensive offload value of application components using the CRITIC weight method and offloading application components with high energy consumption requirements to the edge server while dealing with various task execution delays.The test results suggest that the proposed technique can successfully minimize terminal equipment energy consumption while also improving the overall performance of the terminal equipment.3.The load balancing-based edge server computing task offloading strategy is proposed in the edge server layer to avoid load imbalance produced by the unequal distribution of computing tasks in edge servers.The status information calculates the load balance after the computing tasks are offloaded to the edge server.The task offloading energy consumption ratio determines the offloading priority.According to the priority and task execution delay limits,computational tasks are offloaded to the collaborative edge server.The experiment results show that the system can enhance the load balance of the edge server layer significantly.This thesis offers two computing task offloading strategies and writes algorithms in the Edge Cloud Sim platform to assess their effectiveness,starting with energy consumption of terminal equipment and load balancing of edge servers.The simulation results demonstrate that the proposed terminal device task offloading approach may significantly reduce terminal device energy consumption,while the edge server task offloading strategy can significantly enhance edge server load balance.