LOW OVERHEAD CLUSTERING APPROACH FOR LONG LIFETIME OBJECT TRACKING APPLICATIONS

A.MAHANI, A.MAHANI and M., MIRSADEGHI, and Y.S., KAVIAN (2014) LOW OVERHEAD CLUSTERING APPROACH FOR LONG LIFETIME OBJECT TRACKING APPLICATIONS. In: Second International Conference on Advances in Computing, Electronics and Communication - ACEC 2014, 25 - 26 October 2014, Zurich, Switzerland.

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Abstract

Target tracking is one of the most important applications of wireless sensor networks (WSNs), especially for the urgent event of interest. In this paper we propose a new clustering algorithm beside our accurate prediction mechanism which was proposed previously, that detects and tracks a moving target, and alerts head nodes along the predicted path of the target. The main advantages of proposed clustering algorithms are low transmission overheads with high coverage. Then based on the accuracy of the predictor the best cluster is selected to make more accurate tracking while reducing dramatically the object miss ratio. According to our proposed method in each time instant, only some nodes which, are near to the target and have short distance to the head node, will be selected for tracking and other nodes go to the power saving mode which can strongly reduces the consumed energy.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Target tracking, Wireless sensor networks, Cliustering, Coverage, energy efficiency
Depositing User: Mr. John Steve
Date Deposited: 30 May 2019 10:17
Last Modified: 30 May 2019 10:17
URI: http://publications.theired.org/id/eprint/3063

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