Clustering-Biased Random Algorithm for Load Balancing C-BRALB in wireless sensor networks

Authors:
Barra Touray;Jie Lau;P. Johnson
Affiliations:
Faculty of Technology and Maritime Operations, Department of Engineering, University of Liverpool John Moores University, Byrom Street L3 3AF, UK;Faculty of Technology and Maritime Operations, Department of Engineering, University of Liverpool John Moores University, Byrom Street L3 3AF, UK;Faculty of Technology and Maritime Operations, Department of Engineering, University of Liverpool John Moores University, Byrom Street L3 3AF, UK
Venue:
International Journal of Intelligent Systems Technologies and Applications
Year:
2013

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Abstract

A Wireless Sensor Network WSN consists of large collection of minute nodes organised into a cooperative network used for gathering data in diverse environments. The data collected is transmitted by the sensors to the Sink with the help of a routing algorithm. The energy consumption is a key design criterion for WSN routing algorithms. In this paper Clustering-Biased Random Algorithm for Load Balancing C-BRALB in WSNs is proposed. The clustering technique used in C-BRALB is adopted from the clustering technique used in Improved Directed Diffusion IDD while the routing mechanism is based on energy biased random walk. It is shown in this paper using simulation that C-BRALB is energy efficient, scalable and can load balance the traffic among nodes.