CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

An Energy Efficient Regenerative Techniques for Wireless Sensor Networks

by J. Jasper Gnana Chandran, S. P. Victor
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 10
Year of Publication: 2012
Authors: J. Jasper Gnana Chandran, S. P. Victor
10.5120/5581-7689

J. Jasper Gnana Chandran, S. P. Victor . An Energy Efficient Regenerative Techniques for Wireless Sensor Networks. International Journal of Computer Applications. 41, 10 ( March 2012), 48-54. DOI=10.5120/5581-7689

@article{ 10.5120/5581-7689,
author = { J. Jasper Gnana Chandran, S. P. Victor },
title = { An Energy Efficient Regenerative Techniques for Wireless Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 10 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 48-54 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number10/5581-7689/ },
doi = { 10.5120/5581-7689 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:30:17.451082+05:30
%A J. Jasper Gnana Chandran
%A S. P. Victor
%T An Energy Efficient Regenerative Techniques for Wireless Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 10
%P 48-54
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sensor nodes have various energy and computational constraints because of their inexpensive nature and ad hoc method of deployment. Energy saving is one of the fundamental for system design in wireless sensor networks due to limited on-board resources of sensor nodes. In this paper proposes an extensive amount of solutions have been developed to conserve energy in order to extend the lifetime of sensor networks. As regeneration to existing localization techniques, we developed an energy efficient localization method which evaluated on various mobility models and localization is performed by learning movement patterns and their parameters such as velocity and acceleration. Here the regenerative technique is used to analyze and optimize the set of localization algorithms.

References
  1. Chan. K. W. and H. C. So, 2009 "Accurate distributed range-based positioning algorithm for wireless sensor networks," IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 4100–4105.
  2. Cheung. W, H. C. So, W. K. Ma, and Y. T. Chan, 2006 "A constrained least squares approach to mobile positioning: algorithms and optimality," EURASIP Journal on Applied Signal Processing, vol. 2, Article ID 20858, pp. 23.
  3. Costa. A, N. Patwari, and A. O. Hero III, 2006 "Distributed weighted-multidimensional scaling for node localization in sensor networks," ACM Transactions on Sensor Networks, vol. 2, no. 1, pp. 39–64.
  4. Drineas. P. , A. Javed, M. Magdon-Ismail, G. Pandurangan, R. Virrankoski, and A. Savvides, 2006 "Distance matrix reconstruction from incomplete distance information for sensor network localization," in Proceedings of the 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks (Secon '06), vol. 2, pp. 536–544.
  5. Khan. A, S. Kar, and J. M. F. Moura, 2009 "Distributed sensor localization in random environments using minimal number of anchor nodes," IEEE Transactions on Signal Processing, vol. 57, no. 5, pp. 2000–2016.
  6. Lui. K. W. K. , F. K. W. Chan, and H. C. So, 2009 "Semidefinite programming approach for range-difference based source localization," IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1630–1633.
  7. Lui. K. W. K. , W. -K. Ma, H. C. So, and F. K. W. Chan, 2009 "Semi-definite programming algorithms for sensor network node localization with uncertainties in anchor positions and/or propagation speed," IEEE Transactions on Signal Processing, vol. 57, no. 2, pp. 752–763.
  8. Sun. M. and K. C. Ho, 2009 "Successive and asymptotically efficient localization of sensor nodes in closed-form," IEEE Transactions on Signal Processing, vol. 57, no. 11, pp. 4522–4537.
  9. Tseng. P, 2007 "Second-order cone programming relaxation of sensor network localization," SIAM Journal on Optimization, vol. 18, no. 1, pp. 156–185.
  10. Wang T, G. Leus, and L. Huang, 2009 "Ranging energy optimization for robust sensor positioning based on semi definite programming," IEEE Transactions on Signal Processing, vol. 57, no. 12, pp. 4777–4787.
  11. Wang T, G. Leus, D. Neirynck, F. Shu, and L. Huang, "Ranging energy optimization for robust sensor positioning, 2009 " in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '09), pp. 2237–2240.
  12. Whitehouse. K. , C. Karlof, and D. Culler, 2007 "A practical evaluation of radio signal strength for ranging-based localization," ACM SIGMOBILE Mobile Computing and Communications Review, , vol. 11, no. 1, pp. 41–52.
  13. Yang. K. , G. Wang, and Z. Q. Luo, 2009 "Efficient convex relaxation methods for robust target localization by a sensor network using time differences of arrivals," IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2775–2784.
  14. Zein-Sabatto. Z, V. Elangovan, W. Chen, and R. Mgaya, 2009 "Localization strategies for large-scale airborne deployed wireless sensors," in Proceedings of IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM '09), pp. 9–16.
Index Terms

Computer Science
Information Sciences

Keywords

Regenerative Technique Received Signal Strength

Powered by PhDFocusTM