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Energy efficient grid‐based routing in wireless sensor networks

Energy efficient grid‐based routing in wireless sensor networks Purpose – The purpose of this paper is to explore grid‐based routing in wireless sensor networks and to compare the energy available in the network over time for different grid sizes. Design/methodology/approach – The test area is divided into square‐shaped grids of certain length. Energized nodes are placed randomly in the terrain area with the sink node in a fixed position. One node per grid is elected as the leader node based on the highest energy level and the proximity to the centre of the grid. The sink node floods the network to identify a path from sink to source. The path from the sink to the source through the leader nodes are computed using three different methods: shortest path; leader nodes which have the highest energy; and leader nodes based on their received signal strength (RSS) indicator values. After the path is computed, transmission of data is continued until the leader nodes run out of energy. New leader nodes are then elected using the same mechanism to replace the depleted ones. Findings – Identified the optimal grid size to minimize the energy consumption in sensor networks and to extend the network lifetime. Also proposed is a new routing protocol which identifies routes based on energy threshold and RSS threshold. Research limitations/implications – The use of RSS threshold is identified to be the good metric for path selection in routing the data between source and the sink. Practical implications – Simulator software and the protocol developed can be used for in optimizing energy efficiency in sensor networks. Originality/value – This work contributes to the discussion on uniform and non‐uniform grid sizes and emphasizes a new method for reducing the energy consumption by identifying an optimum grid size. It also utilizes bursty data for simulation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Computing and Cybernetics Emerald Publishing

Energy efficient grid‐based routing in wireless sensor networks

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Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
1756-378X
DOI
10.1108/17563780810874753
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to explore grid‐based routing in wireless sensor networks and to compare the energy available in the network over time for different grid sizes. Design/methodology/approach – The test area is divided into square‐shaped grids of certain length. Energized nodes are placed randomly in the terrain area with the sink node in a fixed position. One node per grid is elected as the leader node based on the highest energy level and the proximity to the centre of the grid. The sink node floods the network to identify a path from sink to source. The path from the sink to the source through the leader nodes are computed using three different methods: shortest path; leader nodes which have the highest energy; and leader nodes based on their received signal strength (RSS) indicator values. After the path is computed, transmission of data is continued until the leader nodes run out of energy. New leader nodes are then elected using the same mechanism to replace the depleted ones. Findings – Identified the optimal grid size to minimize the energy consumption in sensor networks and to extend the network lifetime. Also proposed is a new routing protocol which identifies routes based on energy threshold and RSS threshold. Research limitations/implications – The use of RSS threshold is identified to be the good metric for path selection in routing the data between source and the sink. Practical implications – Simulator software and the protocol developed can be used for in optimizing energy efficiency in sensor networks. Originality/value – This work contributes to the discussion on uniform and non‐uniform grid sizes and emphasizes a new method for reducing the energy consumption by identifying an optimum grid size. It also utilizes bursty data for simulation.

Journal

International Journal of Intelligent Computing and CyberneticsEmerald Publishing

Published: Jun 6, 2008

Keywords: Wireless; Sensors; Radio networks; Signal processing; Energy management

References