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An Optimized Analysis of Localization Algorithm in Wireless Sensor Networks

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Abstract

Determining the position of the sensor node is the ultimate challenging one in wireless sensor networks (WSNs), which may perhaps lead a large localization error. To tackle this tricky, a novel Semi Definite Programming (SDP)—Multiplier method is proposed using time difference of arrival (TDOA) measurement in asynchronous networks. The SDP relaxation method is derived to prevaricate the optimal maximum likelihood (ML) convergence problem that will result in Lagrangian problem. Consequently, this problem can be optimally solved in a stress-free method which provides the value of multipliers. In this Relax and cut scheme, Lagrangian multiplier added in the objective function which gives the minimum value of the function that fulfills the relaxed constraints and reduce the execution time. Also to monitor the mobile target and to improve the energy of sensors, an optimization framework of selective approach algorithm has been used. The simulation result demonstrates that the proposed algorithm provides a better position estimation with less localization error and energy consumption.

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Authors and Affiliations

  1. Research scholar, Sathyabama University, Chennai, 600 119, India

    Z. Mary Livinsa

  2. Adhiparasakthi Engineering College, Melmaruvathur, Kanchipuram District, Tamil Nadu, 603319, India

    S. Jayashri

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  1. Z. Mary Livinsa
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  2. S. Jayashri
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Correspondence to Z. Mary Livinsa.

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Livinsa, Z.M., Jayashri, S. An Optimized Analysis of Localization Algorithm in Wireless Sensor Networks. Wireless Pers Commun 96, 1419–1435 (2017). https://doi.org/10.1007/s11277-017-4247-7

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  • DOI: https://doi.org/10.1007/s11277-017-4247-7

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