Dynamic cluster head selection in wireless sensor network for Internet of Things applications

Internet of things (IoT) integrate the technologies such as sensing, communication, networking and cloud computing in wide range monitoring zone. For applications of IoT, the most appropriate monitoring network is wireless sensor networks (WSN). It is most important to develop energy efficient cluster head (CH) selection scheme to increase the network lifetime of WSNs. It is most crucial to save the energy of these sensor nodes to avoid quick battery drain. In this work, a dynamic CH selection method (DCHSM) is proposed to extend the network lifetime of the systems developed for IoT applications. At first the concept of Voronoi diagram is utilized to divide the large scale monitoring area into small clusters in order to ensure maximum coverage and then the CH is selected in two stages. The first stage of the CH selection is based on perceived probability and the second stage is based on the survival time estimation. Results depicts that the new work performs better than existing algorithms with regard to energy saving and network lifetime for the IoT systems.