a new adaptive approach for efficient energy consumption in edge computing

Edge computing is an evolving approach for the growing computing and networking demands from end devices and smart things. edge computing lets the computation to be offloaded from the cloud data centers to the network edge for lower latency, security, and privacy preservation. although energy efficiency in cloud data centers has been widely studied, energy efficiency in edge computing has been left uninvestigated. in this paper, a new adaptive and decentralized approach is proposed for more energy efficiency in edge environments. in the proposed approach, edge servers collaborate with each other to achieve an efficient plan. the proposed approach is adaptive, and consider workload status in local, neighboring and global areas. the results of the conducted experiments show that the proposed approach can improve energy efficiency at network edges. e.g. by task completion rate of 100%, the proposed approach decreases energy consumption of edge servers from 1053 kwh to 902 kwh.