Green Internet of Things (IoT) with dynamic sleep wake-up approach for constrained things

Abstract

Energy consumption has now become a big deal to ensure the dependability of the IoT. Therefore, minimization of energy consumption is the biggest challenge in IoT architecture. IoT devices are supported with constrained parameters like battery, memory as well as computing. This paper gives a depth analysis of battery-powered things and their green implementation with dynamic Sleep, Wake-up approach based on a decision-making process supported by highly specified data analysis. The proposed method is based on an Energy-Efficient Cluster Head-Based Sleep Scheduling Mechanism (ECHSSM) for efficient Sleep, Wake-up monitoring with dynamic changes in time duration. The architectural prototype for the application scenario for humidity and temperature is studied. The implementation of the model is done by the Cooja simulator. The effectiveness of the proposed strategy is examined using some parameters, such as the lifetime of the network, packet delivery ratio, energy consumption, battery level, and delay characteristic. The proposed technique improves the network lifetime by 11.95%, 7.59%, and 3.83% better than EEHC, LEACH, and cloud-IoT integrated models.