State of Health Optimization Based Unequal Clustering in IoT Networks

Energy optimization is an imminent worldwide issues for green computing, it constitutes a major concern and a critical aspect especially for energy constrained wireless networks. To overcome this issue, clustering techniques were introduced as a prominent method that arranges the system operation in correlated manner to attend the energy preservation and prolong the network lifespan. However, existing clustering works only focus on preserving the battery charge to operate until it drains out. This approach is most appropriate for non-rechargeable batteries. However, rechargeable batteries become commonly used and need to be considered. The full discharge of rechargeable battery does not mean the device obsolescence. Therefore, the system lifetime optimization should take into consideration the degradation of the rechargeable batteries performances. In this context, we proposed an improved long-term energy efficient unequal clustering approach based on the battery state of health for IoT networks (ILEC_SOH). This work represents an initial step in the integration of the battery health degradation into the unequal network clustering. The obtained results show that the consideration of battery state of health (SOH) significantly improve the network lifespan in the long term compared to the conventional energy efficient approaches.