A Binary Hybrid Grey Wolf Optimizer for MEC Offloading
Min Zhang · 2022
Resource allocation plays an important role in mobile edge computing (MEC) networks. However, the optimization of resource allocation is a mixed-integer non-linear programming (MINLP) problem. Due to its NP-hard characterization and shortcomings of traditional methods, solving such kind of problem is challenging. The original grey wolf optimizer (GWO) combined with particle swarm optimization (PSO) is appropriate for continuous problem but limited to the binary problem. The proposed BHGWO algorithm effectively combines the advantages of binary version of the PSO algorithm and GWO algorithm, and improves the optimization efficiency while maintaining the accuracy. Furthermore, a penalty method is introduced to the algorithm. Experiments demonstrate that the proposed algorithm can achieve better performance for MEC computation offloading in terms of system overhead and system utility.