An Integrated Algorithm to Achieve the Best Cluster-Heads in Wireless Sensor Networks

Abstract

Due to the increasing applications of wireless sensor networks (WSN) and the introduction of a new challenge in this regard, offering an algorithm is necessary to maintain and extend the life of network. To this end, offering a mechanism to determine the appropriate cluster head and timely switching is highly important. Since energy is an important challenge in WSNs, using clustering models can be considered as a solution. Selecting appropriate head cluster leads to considerably reduced energy consumption in these networks, leading to increased network lifetime. Different from  previous studies, this article aims to employ a creative method and fuzzy logic to maintain and select the best head clusters. The simulation results showed that the proposed method was associated with condition improvement in most cases. This algorithm is also capable of mixing with all three algorithms including Low Energy Adaptive Clustering Hierarchy (LEACH), weighted energy efficient clustering (WEEC), and General Low Energy Adaptive Clustering Hierarchy (G-LEACH) which is considered as a noticeable advantage. Therefore, using this algorithm leads to delayed death of the first node. As a result, network energy is appropriately consumed. The number of network lost packets is far lower than other algorithms due to cluster head death prevention.