LTEOC: Long Term Energy Optimization Clustering For Dynamic IoT Networks

Mobile traffic is expected to grow by 30% by 2024, saving energy is a crucial necessity even for battery-powered devices such as smartphones for the sake of green computing. Clustering techniques were introduced to conserve the energy of network devices. However, proposed energy optimization techniques do not yield optimal battery life, they mostly consider devices with non-rechargeable batteries and deal with limited energy without considering battery aging (short-term vision). To this end, we focus on the long-term energy optimization and we introduce a dynamic clustering technique that take into consideration the state of health of devices batteries and their degradation level. The proposed scheme efficiently manages the energy resource to enhance the battery behavior which extends the network lifespan in the long term.Simulations results show that the proposed approach out-performs similar works available in the current literature. The batteries life cycle and the network lifetime are improved by 38% and 47% respectively. The average number of generated clusters is reduced by 39%.