Dynamic clustering based energy optimization for iot network

Abstract

The arrival of modern 5G networks is expected to witness a massive increase in internet connections and base stations. Energy optimization is one of the imminent worldwide issues for green computing. Most of the energy efficiency existing works only focus on short-term vision of energy consumption and fails to contemplate the rechargeable battery degradation when evaluating the network lifetime. In this context, we introduce LTE2C, a new Long-Term Energy Efficient Clustering approach for dynamic IoT networks. The objective is to consider the batteries’ degradation process and its state of health (SoH) to improve the network lifetime in long-term and reduces the number of required Internet connection. Several simulation scenarios have been conducted to analyze the performance of our clustering scheme. The obtained results show that the proposal reduces the clusters cardinality and significantly improves the network lifetime in long-term.