@article{(Open Science Index):https://publications.waset.org/pdf/14758,
	  title     = {Effect of Clustering on Energy Efficiency and Network Lifetime in Wireless Sensor Networks},
	  author    = {Prakash G L and  Chaitra K Meti and  Poojitha K and  Divya R.K.},
	  country	= {},
	  institution	= {},
	  abstract     = {Wireless Sensor Network is Multi hop Self-configuring
Wireless Network consisting of sensor nodes. The deployment of
wireless sensor networks in many application areas, e.g., aggregation
services, requires self-organization of the network nodes into clusters.
Efficient way to enhance the lifetime of the system is to partition the
network into distinct clusters with a high energy node as cluster head.
The different methods of node clustering techniques have appeared in
the literature, and roughly fall into two families; those based on the
construction of a dominating set and those which are based solely on
energy considerations. Energy optimized cluster formation for a set
of randomly scattered wireless sensors is presented. Sensors within a
cluster are expected to be communicating with cluster head only. The
energy constraint and limited computing resources of the sensor nodes
present the major challenges in gathering the data. In this paper we
propose a framework to study how partially correlated data affect the
performance of clustering algorithms. The total energy consumption
and network lifetime can be analyzed by combining random geometry
techniques and rate distortion theory. We also present the relation
between compression distortion and data correlation.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {7},
	  year      = {2009},
	  pages     = {1812 - 1817},
	  ee        = {https://publications.waset.org/pdf/14758},
	  url   	= {https://publications.waset.org/vol/31},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 31, 2009},
	}