CFP last date
21 October 2024
Reseach Article

A New Adaptive Target Tracking Protocol in Wireless Sensor Networks

by Elham Ahmadi, Masoud Sabaei
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 10
Year of Publication: 2011
Authors: Elham Ahmadi, Masoud Sabaei
10.5120/3422-4185

Elham Ahmadi, Masoud Sabaei . A New Adaptive Target Tracking Protocol in Wireless Sensor Networks. International Journal of Computer Applications. 28, 10 ( August 2011), 5-11. DOI=10.5120/3422-4185

@article{ 10.5120/3422-4185,
author = { Elham Ahmadi, Masoud Sabaei },
title = { A New Adaptive Target Tracking Protocol in Wireless Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 10 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number10/3422-4185/ },
doi = { 10.5120/3422-4185 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:14:24.657694+05:30
%A Elham Ahmadi
%A Masoud Sabaei
%T A New Adaptive Target Tracking Protocol in Wireless Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 10
%P 5-11
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In wireless sensor networks sampling time interval and the number of nodes involved in each stage of tracking are important factors which have high effect on the efficiency of target tracking applications. In this paper a new target tracking method has been proposed which at each time step employs two helpful tools. First, an extended Kalman filter (EKF)-based estimation technique to predict the tracking error and second, an energy consumption model to estimate energy consumption based on different number of nodes and sampling time intervals. By using these estimations, this method selects the best number of nodes and sampling time interval according to an objective function which is defined based on tracking accuracy and energy consumption.

References
  1. H. W. Tsai, C. P. Chu, T. S. Chen, “Mobile object tracking in wireless sensor networks,” Computer Communication, 2007, 30(8): 1811-1825.
  2. E. Ahmadi, M. Sabaei, M. H. Ahmadi “A New Adaptive Method for Target Tracking in Wireless Sensor Networks”, International Journal of Computer Applications, volume22, No.9, 2011, pp.21-29.
  3. Sara Pino-Povedano, Francisco-Javier Gonzalez Serrano, “Distributed Tracking and Classification of Targets with Sensor Networks,” IEEE 2009.
  4. Z. Guo, M. Zhou and L. Zakrevski, "Optimal Tracking Interval for predictive Tracking in wireless Sensor Networks," IEEE Communication Letters, vol. 9, No.9, Sept 2005.
  5. L. Yang, C. FENG, J. W. Rozenblit , and H. Qiao, "Adaptive Tracking in distributed Wireless Sensor Networks," in proc. Of 13th Annual IEEE International Symposium and Workshop on Engineering of Computer Based Systems, pp. 9, Mar. 2006.
  6. H. Jamali Rad, B. Abolhassani and M. Abidzadeh, "A new Adaptive Prediction–based Tracking Scheme for Wireless Sensor Networks ,"Proc. Of 7th Annual conference on communication Networks and System Research(CNSR09) , pp. 335-341, May, 2009.
  7. W. Xiao, Sen. Zhang, J. Lin, C. K.Tham, "Energy-efficient adaptive sensor scheduling for target tracking in wireless sensor networks", J Control Theory Appl, 2010, vol. 8, No. 1, pp.86-92.
  8. M. Kalandros, L. Pao. Covariance control for multisensor systems
  9. J .IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(4): 1138 – 1157.
  10. HyunSook, K; Eunhwa, K; Kijun,H. An Energy Efficient Tracking Method in Wireless Sensor Networks. In Next Generation Teletraffic and Wired/Wireless Advanced Networking, Publisher: Springer Berlin / Heidelberg, 2006;4003, pp. 278- 286.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless sensor networks target tracking energy consumption tracking error