CE2RV: Commissioned energy‐efficient virtualization for large‐scale heterogeneous wireless sensor networks

Abstract

SummaryThe Internet of Things (IoT) comprises sensor networks, intelligent things, devices, and humans for heterogeneous services and applications. Energy constraints in conventional wireless networks impact IoT performance resulting in service failures. For reducing the adverse impact of energy, this article introduces a commissioned energy‐efficient resource virtualization (CE2RV) scheme. This proposed scheme classifies the sensor nodes as fast and slow‐depleting for identifying service failures. The fast‐depleting nodes are discontinued from the service replications, and the remaining energy high‐node‐connected resources are identified. Such resources are virtualized for thwarting the existing energy failures over various services. The node classifications are performed using a tree‐learning algorithm. The classifications are performed for node replacement and service virtualization under different energy depletion rates. This is required for preventing sensor network disconnections between the users and service providers. The classification is required for overcoming multiple virtualizations between common nodes across different service providers. The proposed scheme's performance is analyzed using the metrics of service disconnections, energy utilization, energy efficiency, and service delay.