A Hybrid Heuristic Task Offloading Algorithm in Mobile Edge Computing for Joint Optimization of Delay and Energy Consumption

A Hybrid Heuristic Task Offloading Algorithm in Mobile Edge Computing for Joint Optimization of Delay and Energy Consumption

연구 분야: Networking

학회: Journal of Network and Systems Management

The advent of mobile edge computing has given rise to a pressing concern: the optimal methodology for offloading edge computing tasks. Edge computing provides computing and storage capabilities at the edge of the network, in close proximity to the user. Through process of computation offloading, tasks that would otherwise be performed by the terminal are migrated to edge servers for execution, this has potential to significantly reduce application latency and conserve terminal energy consumption. Nevertheless, the majority of current significant research on task offloading for mobile edge environments focuses on the latency or energy consumption of a single mobile terminal. Accordingly, a hybrid heuristic task offloading algorithm based on integer coding is put forth for edge computing environments comprising multiple edge servers and multiple mobile terminals. The completion time of the task and the weighted calculation of energy consumption of the terminal were used as evaluation indexes. Based on the concepts of individual historical optimization and global optimization of the Improved Particle Swarm Optimization(IPSO) algorithm, four chemical molecular operations simulated by chemical reaction optimization (CRO) algorithm were introduced, so that molecules could be continuously optimized in the process of chemical reaction. The results of comparative simulation experiments demonstrate that compared with classical algorithms such as the IPSO algorithm, CRO algorithm and newer algorithms, IPSO_CRO algorithm can obtain better unloading decisions, and the optimization of objective function values, namely energy consumption and delay, is significantly better than other algorithms.