Energy-Efficient Traffic in Cloud-Based IoT

Abstract

IoT is being increasingly used to enable continuous monitoring and sensing of physical things in the world. Energy efficiency is a critical aspect in its design and deployment, as IoT devices are usually battery-powered, and it is difficult, expensive, or even dangerous to replace the batteries in many real physical environments. In this paper, an energy-efficient cloud-based IoT network model has been created by optimizing sensor selection, selecting the least number of hops, and leveraging fading subchannel gain to reduce traffic power and cancel interference. Using the MILP, the optimization model and results are determined. The model assesses the outcomes of two possible scenarios: First, network optimization for energy efficiency based on the least number of hops, followed by a comparison with the second scenario. Second, energy-efficient network optimization by minimizing hops and selecting sub-channels. The results indicate that the first scenario consumes more network traffic power in IoT devices, whereas the second scenario reduces network traffic power by an average of 27 percent.