Data Aggregation for Failure Tolerance in Wireless Sensor Network

Na Wang; Yue Ping Wu

doi:10.4028/www.scientific.net/AMM.347-350.965

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350Data Aggregation for Failure Tolerance in Wireless...

Data Aggregation for Failure Tolerance in Wireless Sensor Network

Abstract:

One of the critical tasks in designing a wireless sensor network is to monitor, detect, and report various useful occurrences of events in the network domain which are determined by the result of data aggregation. Fault tolerance is critical to the efficiency of data aggregation scheme. One important reason is that sensor nodes are neither reliable nor stabile. In this paper, we present an improved k-means data aggregation algorithm considering the proposal of isolated point. Each cluster includes three types of sets: aggregation data, fault data set and abnormal data set. Aggregation data comes from normal sensors in this cluster through the improved K-means aggregation algorithm and abnormal nodes can be detected according to the aggregation result.

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

Pages:

965-969

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.347-350.965

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Online since:

August 2013

Authors:

Na Wang, Yue Ping Wu

Keywords:

Abnormal Node, Data Aggregation, Data Set, K-Mean, Wireless Sensor Network (WSN)

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References

[1] Giuseppe Di Fatta. Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks. J. Parallel Distrib. Compute 2012. 09. 009.

DOI: 10.1016/j.jpdc.2012.09.009

Google Scholar

[2] Yunxia Feng, Shaojie Tang, Guojun Dai. Fault Tolerant Data Aggregation Scheduling with Local Information in Wireless Sensor Networks. TSINGHUA SCIENCE AND TECHNOLOGY, Volume 16, Number 5, October (2011).

DOI: 10.1016/s1007-0214(11)70065-7

Google Scholar

[3] XIAO Wei, XU Ming. Fault tolerant scheme for data aggregation in event cluster over wireless sensor networks. Journal on Communications, Vol. 31 No. 6, June (2010).

Google Scholar

[4] Donggook Kim. An event-aware MAC scheduling for energy efficient aggregation in wireless sensor networks. Computer Networks 55 (2011) 225-240.

DOI: 10.1016/j.comnet.2010.08.010

Google Scholar

[5] Laukik Chitnis, Alin Dobra, Sanjay Ranka. Analyzing the techniques that improve fault tolerance of aggregation trees in sensor networks. on Embedded Network Sensor Systems. J. Parallel Distrib. Comput. 69 (2009) 950-960.

DOI: 10.1016/j.jpdc.2009.04.013

Google Scholar

[6] MaheshKumar, ShishirKumar. Asustainableandfaulttolerantaggregation. Journal ofNetworkand Computer Applications 2012. 10. 009.

Google Scholar