Publication Type : Conference Paper
Thematic Areas : Wireless Network and Application
Publisher : Proceedings of the 2008 International Conference on Wireless Networks, ICWN 2008, Las Vegas, NV, 2008.
Source : Proceedings of the 2008 International Conference on Wireless Networks, ICWN 2008, Las Vegas, NV, 2008, pp. 107-113.
ISBN : 1601320914; 9781601320919
Keywords : Approximation theory, Area monitoring, cluster analysis, Cluster heads, Clustering, Clustering approaches, Code predictions, Electromagnetic compatibility, Electromagnetic pulse, Energy efficiency, Energy-efficient, Environmental hazards, Error approximations, Failed nodes, Fault tolerance, Fault-tolerant, Landslide predictions, Landslides, matrixes, Processing overheads, Quality assurance, Real-world applications, Safety critical applications, Sensor datum, Sensor networks, Sensor nodes, Telecommunication equipment, Wireless sensor networks, Wireless telecommunication systems, WSN
Campus : Amritapuri
School : School of Engineering
Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)
Department : Computer Science
Year : 2008
Abstract : The installation or deployment of a wireless sensor network (WSN) in a real world application is prone to innumerable failures such as software or hardware malfunctioning, environmental hazards, radio interference, battery exhaustion, etc. In a safety critical application such as landslide prediction, fault tolerant approaches have to be followed to ensure the availability of sensor data at the analysis station during a critical situation. We propose a fault tolerant and energy efficient clustering approach which organizes the whole network into smaller cluster and subcluster groups enabling a considerable reduction of communication and processing overhead. Subcluster formation also gives the possibility to skillfully deal with sensor nodes, node leader, and cluster head failures. We also propose a fault tolerant approach that uses a matrix based error approximation method for providing the approximate sensor data of the failed node. The approximate code prediction takes into consideration various geological aspects of the problem.
Cite this Research Publication : R. R. T., Dr. Maneesha V. Ramesh, and Sangeeth, K., “Fault Tolerant Clustering Approaches in Wireless Sensor Network for Landslide Area Monitoring”, in Proceedings of the 2008 International Conference on Wireless Networks, ICWN 2008, Las Vegas, NV, 2008, pp. 107-113.
