Authors: Navdeep Singh; Rakesh Kumar
Addresses: GMUADM, Infosys Ltd., Pune, India ' Department of CSE, NITTTR, Chandigarh, India
Abstract: Rate of occurrence of high-dimensional data is much higher and sad to relate, classical clustering techniques do not hold good for such high-dimensional networks of arbitrary shapes in the underwater wireless sensor network. This is mainly due to the fact that clustering techniques are highly parameterised. Data aggregation using traditional clustering techniques is a problem for high-dimensional network because of its arbitrary shapes. Moreover, existing clustering algorithms cannot be used for solving the problem and enhancing clustering performance. Numerous top-notch researchers have employed fuzzy logic-based clustering schemes in the past. We analyse these techniques to find scientific tendency. In this paper, a fuzzy-based algorithm for clustering ensemble is proposed where sensor nodes are characterised based upon major and minor criteria. This algorithm is developed to group the sensor nodes in multiple clusters. The clustering precision is designed to assess the efficacy of the algorithm. This algorithm also competes in its ability to distinguish the difference between all the sensor nodes present in the network. Other clustering algorithms in existence for data aggregation are also reviewed and compared with the proposed technique.
Keywords: fuzzy set theory; UWSN; underwater sensor networks; sensor nodes; network optimisation; data aggregation; data clustering; trapezoidal fuzzy numbers; linguistic variables; fuzzy logic; clustering algorithms; node clusters.
International Journal of Systems, Control and Communications, 2016 Vol.7 No.2, pp.132 - 150
Available online: 30 May 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article