Article citationsMore>>

S. Ray and R. H. Turi, “Determination of Number of Clusters in K-Means Clustering and Application in Colour Image Segmentation,” Image, In: N. R. Pal, A. K. De and J. Das, Eds., Proceedings of the 4th International Conference on Advances in Pattern Recognition and Digital Techniques, Calcutta, 27-29 December, 1999.

has been cited by the following article:

• TITLE: Multiple Parameter Based Clustering (MPC): Prospective Analysis for Effective Clustering in Wireless Sensor Network (WSN) Using K-Means Algorithm

  AUTHORS: Md. Asif Khan, Israfil Tamim, Emdad Ahmed, M. Abdul Awal

  KEYWORDS: K-Means Algorithm; Energy Efficient; Uniform Distribution; RSSI; Latency

  JOURNAL NAME: Wireless Sensor Network, Vol.4 No.1, January 4, 2012

  ABSTRACT: In wireless sensor network cluster architecture is useful because of its inherent suitability for data fusion. In this paper we represent a new approach called Multiple Parameter based Clustering (MPC) embedded with the traditional k-means algorithm which takes different parameters (Node energy level, Euclidian distance from the base station, RSSI, Latency of data to reach base station) into consideration to form clusters. Then the effectiveness of the clusters is evaluated based on the uniformity of the node distribution, Node range per cluster, Intra and Inter cluster distance and required energy level of each centroid. Our result shows that by varying multiple parameters we can create clusters with more uniformly distributed nodes, minimize intra and maximize inter cluster distance and elect less power consuming centroid.