Green Communication: Optimal Charger Deployment based on TBM (OCD-TBM) in IoT

Towards Green communication, wireless Power transfer technology is a convenient and reliable method designed for supply power to energy scare Internet of Things nodes. This technique efficiently solves the finite battery power problem of the nodes. Previously proposed models on optimal charger deployment have not considered the effect of data traffic distribution in the network pertain to energy consumption of devices. Traffic distribution causes nonuniform energy consumption of nodes turnout to deteriorate the network performance. In this context, we propose a model to find optimal location for charger deployment based on transferable belief model (TBM). Further, placement of charger is determined that provide maximum energy in the IoT network over traffic flow and TBM. Furthermore, an algorithm optimal charger deployment based on TBM (OCD-TBM) is presented to find the optimal number of chargers to be deployed in the IoT network. The presented algorithm optimizes the network performance in terms of energy cost in effective way by increasing the network lifetime. Extensive simulation is performed to show the robustness of proposed algorithm by varying network size and charger placement angle. Further, comparative analysis from random deployment approach shows that proposed OCD-TBM outperforms in terms of charger deployment with less numbers than that of traditional approach.