Energy efficient multi-tasking for edge computing using federated learning

Abstract

Purpose The purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage. Design/methodology/approach The new greedy algorithm is proposed to balance the energy consumption in edge computing. Findings The new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent. Originality/value The results are shown in this paper which are better as compared to existing algorithms.