An Efficient Computing Task Offloading Strategy Based on Energy Consumption and Load Balancing Degree
Nan Hu, Min Xiang, Chunmei Huang, Lingling Qin, Bin Yang, Ruiqiong Wang, Luo Zhang · 2022
Computing tasks offload of the edge computing has a significant impact on edge devices energy consumption and load balancing. To reduce the total cost, an offloading strategy that combines energy consumption and load balancing degree is proposed. A task partitioning model is given to perform fine-grained division of computing tasks. Furthermore, the energy consumption model of computing task offloading is obtained through the time delay model, and then the cost function of computing task offloading is constructed in combination with the load balancing degree and energy consumption. With the task offloading strategy, the minimum cost of task offloading is obtained under the multiple constraints, and the path of computing task offloading is determined. The simulation results demonstrate that the strategy can significantly improve the load balancing of the edge server and the overall performance of the edge server.