Voronoi Fuzzy Clustering Approach for Data Processing in WSN

Abstract

Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent by individual sensor node is minimized. The cluster heads collect all sensed information from their respective cluster members and performs data aggregation to transmit the data to the sink node. In this paper novel Voronoi Fuzzy multi hop clustering (V-FCM) algorithm is proposed for grouping the sensor node. This algorithm is a mixture of Voronoi diagram and modified Fuzzy C- Means clustering algorithm. In addition to clustering, data aggregation technique such as MAX, MIN and AVG is computed in each cluster head for further reduction of the number of data transmissions. Finally, the simulations are performed and the results are analyzed within the simulation set up to determine the performance of the proposed algorithm in Weather forecasting sensor network. Our proposed approach has achieved higher energy efficiency when compared with the Fuzzy C-Means algorithm.

Keywords:

• Clustering
• data aggregation
• Voronoi fuzzy clustering algorithm
• energy
• QoS
• Delaunay triangulation
• EMST