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A. G. Akojwar and R. M. Patrikar, “Improving Life Time of Wireless Sensor Networks Using Neural Network Based Classification Techniques with Cooperative Routing,” International Journal of Communications, Vol. 2, No. 1, 2008, pp.75-86.

has been cited by the following article:

• TITLE: Energy Efficient Computation of Data Fusion in Wireless Sensor Networks Using Cuckoo Based Particle Approach (CBPA)

  AUTHORS: Manian Dhivya, Murugesan Sundarambal, Loganathan Nithissh Anand

  KEYWORDS: Cuckoo Search, Generalized Particle Model, Energy Efficiency, Clustering, Sensor Networks

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.4 No.4, April 15, 2011

  ABSTRACT: Energy efficient communication is a plenary issue in Wireless Sensor Networks (WSNs). Contemporary energy efficient optimization schemes are focused on reducing power consumption in various aspects of hardware design, data processing, network protocols and operating system. In this paper, optimization of network is formulated by Cuckoo Based Particle Approach (CBPA). Nodes are deployed randomly and organized as static clusters by Cuckoo Search (CS). After the cluster heads are selected, the information is collected, aggregated and forwarded to the base station using generalized particle approach algorithm. The Generalized Particle Model Algorithm (GPMA) transforms the network energy consumption problem into dynamics and kinematics of numerous particles in a force-field. The proposed approach can significantly lengthen the network lifetime when compared to traditional methods.