Optimizing computation offloading strategy in mobile edge computing based on swarm intelligence algorithms

Abstract As the technology of Internet Things (IoT) and mobile edge computing (MEC) develops, more tasks are offloaded to servers be computed. The offloading strategy performs an essential role in progress computation offloading. In a general scenario, should consider enough factors, made as quickly possible. While most existing model only considers one or two we investigated considering three targets improved it by normalizing each target eliminate influence dimensions. Then, grey wolf optimizer (GWO) is introduced solve model. To obtain better performance, proposed algorithm hybrid whale optimization (WOA) with GWO named GWO-WOA. And tested on our Finally, results obtained GWO-WOA, GWO, WOA, particle swarm (PSO), genetic (GA) discussed. have shown advantages