An energy efficient fuzzy cluster head selection algorithm for WSNs
In wireless sensor networks (WSNs) tiny sensor nodes are randomly deployed with limited amount of energy to transmit massive data, like images and videos. Related information can be obtained when a CMOS camera is connected to a sensor node to capture images. Thus how to improve energy efficiency and prolong network lifetime is a challenging research issue. Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the network lifetime. However, many existing algorithms select the Cluster Head (CH) randomly based on a probabilistic threshold value or only consider the remaining energy parameter. In this work, we propose a fuzzy cluster head selection algorithm which takes three parameters into consideration, namely node's remaining energy, centrality of the clusters as well as the distance between node and the mobile sink. Simulation results show that our proposed algorithm is superior to other popular algorithms in terms of network lifetime and energy consumption.
2018 International Workshop on Advanced Image Technology (IWAIT)