MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks

• In this paper, a multi-objective fuzzy clustering algorithm (MOFCA) that addresses the hotspots and energy hole problems both in stationary and evolving networks is introduced.
• The MOFCA aims to balance the energy consumption over network by wisely adjusting the cluster competition radius according to three input parameters.
• Like some other studies, a fuzzy approach is adopted to handle uncertainties in cluster-head radius estimation.
• The radius tuning mechanism of MOFCA solves the above-mentioned problems both in stationary and evolving networks.
• MOFCA is a distributed, reliable, scalable, and more efficient clustering algorithm than the compared protocols to be utilized in WSN applications.

This study introduces a new clustering approach which is not only energy-efficient but also distribution-independent for wireless sensor networks (WSNs). Clustering is used as a means of efficient data gathering technique in terms of energy consumption. In clustered networks, each node transmits acquired data to a cluster-head which the nodes belong to. After a cluster-head collects all the data from all member nodes, it transmits the data to the base station (sink) either in a compressed or uncompressed manner. This data transmission occurs via other cluster-heads in a multi-hop network environment. As a result of this situation, cluster-heads close to the sink tend to die earlier because of the heavy inter-cluster relay. This problem is named as the hotspots problem. To solve this problem, some unequal clustering approaches have already been introduced in the literature. Unequal clustering techniques generate clusters in smaller sizes when approaching the sink in order to decrease intra-cluster relay. In addition to the hotspots problem, the energy hole problem may also occur because of the changes in the node deployment locations. Although a number of previous studies have focused on energy-efficiency in clustering, to the best of our knowledge, none considers both problems in uniformly and non-uniformly distributed networks. Therefore, we propose a multi-objective solution for these problems. In this study, we introduce a multi-objective fuzzy clustering algorithm (MOFCA) that addresses both hotspots and energy hole problems in stationary and evolving networks. Performance analysis and evaluations are done with popular clustering algorithms and obtained experimental results show that MOFCA outperforms the existing algorithms in the same set up in terms of efficiency metrics, which are First Node Dies (FND), Half of the Nodes Alive (HNA), and Total Remaining Energy (TRE) used for estimating the lifetime of the WSNs and efficiency of protocols.

This study introduces a new clustering algorithm which is not only more energy-efficient than all compared clustering algorithms but also distribution-agnostic for wireless sensor networks. Figure optionsDownload as PowerPoint slide