A Load-Balanced Clustering Algorithm Using Fuzzy Logic for Maximizing Lifetime of Wireless Sensor Networks

In wireless sensor networks (WSN), clustering has been shown to effectively prolong network lifetime, and unequal clustering, which is an extension to traditional clustering, has demonstrated even better results. In unequal clustering, each individual cluster has a different cluster range. To date, clustering range calculations has been performed based on node positions in the network. However, node fitness is an important parameter. If assigned to a larger cluster range, nodes with low fitness can create inconsistencies within the network. Moreover, these methods fail to incorporate uncertainties in parametric quantities encountered during cluster head (CH) selection and cluster range assignment. Therefore, we propose a fuzzy logic based chance calculation that handles uncertainties in parametric quantities. The calculated chance value is applied for the selection of CHs and the chance value, is used along with node position to assign a proper cluster range. Compared with some well known approaches shows that the proposed approach creates more balanced clusters, consequently extending network lifetime.