Delay Optimization Based on Improved Differential Evolutionary Algorithm for Task Offloading in Fog Computing Networks

With the rapid development of communication technology, more and more devices tend to be intelligent. Intelligent devices with computing functions can provide computing services to reduce total task completion time in fog computing networks. This paper aims at minimizing the total task completion time to study multi-user multi-node multi-task offloading problem. Firstly, the task offloading process of task node and fog node is modeled. Then, the system function of the total task completion time is constructed and an optimization problem with constraints is generated. The problem is NP-hard and difficult to be solved by traditional methods. Finally, the improved differential evolution (IDE) algorithm is used to solve the task offloading problem. Simulation results show that it has better performance and can significantly shorten the total task completion time compared with other algorithms.