Optimization of Task Offloading Problem Based on Simulated Annealing Algorithm in MEC
Ying Li
Abstract
Mobile Edge Computing (MEC) effectively solves the problem of terminal equipment energy consumption and resource limitations by offloading tasks to edge service nodes. In the process of task unloading, it is necessary to make unloading decisions and resource allocation for user tasks. In this paper, the weighted value of time and energy consumption is the optimization goal, and the problem of offloading decision-making and channel allocation in single-task scenarios of multi-users and multi-servers is studied, and an optimization algorithm based on simulated annealing algorithm (SA) is proposed. Experiments verify that the algorithm can flexibly adjust the preference for time and energy consumption according to different application scenarios, effectively improving the overall performance of the system.