Abstract
Edge-of-Things (EoT) emerged as a novel computing and storage paradigm to overcome the limitations of IoT-cloud environment by providing cloud-like services at edge of the network. EoT offers a vast area for research and development as the invention has laid out great opportunities to experiment the possibilities for handling large data sets produced by the growing Internet-of-Things (IoT). The EoT offers a framework that lies between the cloud-to-end to perform the processing and cater the storage demands of the IoT applications. However, the exponential increase in EoT infrastructure resulted into extreme energy consumption. This paper finds the opportunity to address the issue of energy consumption in IoT-EoT environment by introducing dynamic speed scaling mechanism in EoT devices. The proposed approach is rigorously evaluated, and the verification is acquired through the simulations carried out on the simulator, iFogSim. The results show significant improvement in energy conservation by dynamically scaling the processor frequency of EoT devices according to the load variations in IoT traffic.
Highlights
Edge-of-Things (EoT) has emerged in the progressing world of information technology, as a paradigm liable to provide utmost quality of processing and storage services at edge of the network
The dynamic speed controller keeps track of the amount of workload being subjected upon the EoT/fog device by the Internet of Things (IoT) applications, in a way that it alters the speed of the CPU under specified conditions
The comparison of the energy consumption of the system executing in OnDemand mode with the system that executes completely on fog and does not perform any kind of speed scaling is illustrated in the Fig. 4
Summary
Edge-of-Things (EoT) has emerged in the progressing world of information technology, as a paradigm liable to provide utmost quality of processing and storage services at edge of the network. The Internet of Things (IoT) is progressing rapidly offering an infrastructure that is most viable to bring a significant quality enhancement to human life and productivity [1]. The growing advancements in this technology demands a platform that is more energy-efficient and causes lesser delay. IoT devices backbone has two major infrastructures, cloud and fog/edge computing. Both of them significantly provide efficient data storage and resource management, enabling the developers to create interactive Internet service platforms for smart access
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