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HaarWavelet Based Distributed Predictive Target Tracking Algorithm for Wireless Sensor Networks

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Advances in Computational Science, Engineering and Information Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 225))

Abstract

Target tracking is a typical and important application of wireless sensor networks (WSNs). In the consideration of scalability and energy efficiency for target tracking in large scale WSNs, it has been employed as an effective solution by organizing the WSNs into clusters. However, tracking a moving target in cluster-based WSNs suffers many problems e.g. energy consumption and need to use complex predictive tracking. In this paper, we propose a novel scheme, called Haar wavelet-based target tracking (HWDPT). We proposed an efficient prediction algorithm for mobile targets tracking based on Haar Wavelet transform. Also, we integrated on-demand dynamic clustering into a clusterbased WSN for effective target tracking. The simulation results validate that the proposed HWDPT protocol performs better in terms of track failed ratio, energy waste ratio and algorithm complexity, respectively.

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Authors and Affiliations

  1. Electrical, Computer, and IT Department, Qazvin Islamic Azad University, Qazvin, Iran

    Mahsa Ghasembaglou & Abolfazl Toroghihaghighat

Authors
  1. Mahsa Ghasembaglou
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  2. Abolfazl Toroghihaghighat
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Corresponding author

Correspondence to Mahsa Ghasembaglou .

Editor information

Editors and Affiliations

  1. , Dept of Computer Engineering, KTO Karatay University, 130 Karatay, Konya, 42020, Turkey

    Dhinaharan Nagamalai

  2. , School of Computing and Informatics, University of Louisiana at Lafayette, 214 Oliver Hall, Lafayette, 70504-4330, Louisiana, USA

    Ashok Kumar

  3. , Dept. of Electrical &, Prairie View A&M University, Prairie View, 77446-0519, Texas, USA

    Annamalai Annamalai

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Ghasembaglou, M., Toroghihaghighat, A. (2013). HaarWavelet Based Distributed Predictive Target Tracking Algorithm for Wireless Sensor Networks. In: Nagamalai, D., Kumar, A., Annamalai, A. (eds) Advances in Computational Science, Engineering and Information Technology. Advances in Intelligent Systems and Computing, vol 225. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00951-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-00951-3_21

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00950-6

  • Online ISBN: 978-3-319-00951-3

  • eBook Packages: EngineeringEngineering (R0)

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