Research Article Open Access

Advanced Energy Efficient Passive Clustering Mobility in Wireless Sensor Networks

Aouad Siham1, Maach Abdelillah1 and El Ganami Driss1
  • 1 Laboratory Networks and Intelligent Systems, Mohammedia School of Engineering, Univeristy Mohammed V Agdal Rabat, Morocco

Abstract

Wireless sensor networks have a wide applicability and increase deployment in the near future. In most of those applications, the network is composed of an important number of nodes deployed in an extensive area in which not all nodes are directly connected and based on clustering techniques. The Clustering can considerably reduce transmission overhead during flooding. In fact, by using clustering, we minimize the set of forwarding nodes during transmission and consequently reduce the energy cost and traffic overhead in topology environments. In this study, we present passive clustering mechanisms and the main clustering protocols proposed for wireless sensor networks; we also introduce a new protocol designated for mobile nodes in wireless sensor network that is based on the APC-T. This mechanism provides the stability of clusters after each departs of cluster-head and allows balanced energy consumption among the sensor nodes. Comparison with the existing schemes such as APC-T and Geographically Repulsive Insomnious Distributed Sensors (GRIDS) proves that the mechanism for selecting a backup of cluster-head nodes, which is the most important factor influencing the clustering performance, can significantly improves the network lifetime.

American Journal of Applied Sciences
Volume 10 No. 12, 2013, 1558-1569

DOI: https://doi.org/10.3844/ajassp.2013.1558.1569

Submitted On: 30 September 2013 Published On: 24 October 2013

How to Cite: Siham, A., Abdelillah, M. & Driss, E. G. (2013). Advanced Energy Efficient Passive Clustering Mobility in Wireless Sensor Networks. American Journal of Applied Sciences, 10(12), 1558-1569. https://doi.org/10.3844/ajassp.2013.1558.1569

  • 3,023 Views
  • 2,522 Downloads
  • 7 Citations

Download

Keywords

  • Wireless Sensor Networks
  • Clustering Algorithms
  • Self-Organization
  • Energy Efficiency