Recent years have witnessed billions of new manufactured sensors, equipments, and machines being connected to our almost omnipotent Internet. While enjoying the comfort and convenience brought by IoT, we also have to face tremendous energy consumption and carbon emissions that even cause climate deterioration. Extended from cloud computing, edge/fog computing and caching provide new thoughts on processing big data generated from distributed IoT devices. With the purpose of helping deal with the data explosion problem by edge caching, in this article we apply in-memory storage and processing to reduce energy consumption. We design two kinds of TTL in four cache replacement policies to cache data at the edge. We carry out a simulation experiment in a three-tier heterogeneous network structure using the RWP model and test the performance of in-memory caching and the traditional method. The analysis results manifest that our in-memory method is able to obtain better energy efficiency in edge caching, and has stable and low backhaul rate.
In reference REF , Xu et al. proposed an in-memory storage and processing method to reduce energy consumption in a three-tier heterogeneous network architecture.
Saving Energy on the Edge: In-Memory Caching for Multi-Tier Heterogeneous Networks
IEEE Communications Magazine
IEEE Communications Magazine
Computer Science