Collaborative Data Processing in WSN Using Voronoi Fuzzy Clustering

• Published in: International journal of computers, communications & control Vol. 10; no. 3
• Main Authors: Kalyani, S Nithya, Sasikala, E, Gopinath, B
• Format: Journal Article
• Language: English
• Published: Oradea Agora University of Oradea 01.06.2015
• Subjects: Agglomeration; Algorithms; Clustering; Collaboration; Compression; Data compression; Data management; Data mining; Data processing; Decision making; Delay time; Energy efficiency; Nodes; Sensors; Voronoi graphs; Wireless sensor networks
• ISSN: 1841-9836; 1841-9844
• DOI: 10.15837/ijccc.2015.3.96

In this paper, developed a novel Voronoi Fuzzy Clustering (VF) algorithm for energy efficient collaborative data aggregation in wireless sensor network. VF algorithm is fusion of Voronoi diagram and modified Fuzzy C- Means with respect to distance and Quality of Service. Here throughput, delay time and delivery ratio are considered as QOS parameters. Once clustering of sensor nodes is completed then data management technique such as data aggregation or compression is done for further decision making in sink node. Data mining 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 collects all sensed information from their respective cluster members and performs data aggregation or compression before transmitting the data to the sink node. Finally, the simulations are performed and the results are analyzed within the simulation set up to determine performance of the proposed algorithm in the sensor network. Our proposed approach has achieved 60% efficiency when compare with the K means algorithm.