CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Hybrid Data Filtering Approach for Mobile Wireless Sensor Networks

by Kavita Gupta, Aarti Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 138 - Number 8
Year of Publication: 2016
Authors: Kavita Gupta, Aarti Singh
10.5120/ijca2016909022

Kavita Gupta, Aarti Singh . Hybrid Data Filtering Approach for Mobile Wireless Sensor Networks. International Journal of Computer Applications. 138, 8 ( March 2016), 37-41. DOI=10.5120/ijca2016909022

@article{ 10.5120/ijca2016909022,
author = { Kavita Gupta, Aarti Singh },
title = { Hybrid Data Filtering Approach for Mobile Wireless Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 138 },
number = { 8 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume138/number8/24402-2016909022/ },
doi = { 10.5120/ijca2016909022 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:39:11.247748+05:30
%A Kavita Gupta
%A Aarti Singh
%T Hybrid Data Filtering Approach for Mobile Wireless Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 138
%N 8
%P 37-41
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a hybrid data filtering approach for mobile wireless sensor networks. This hybrid approach ensures filtering of data before it is being sent to sink node from the sensor network. Further, this approach reduces amount of noisy data being transferred, thereby increasing network lifetime and reducing rate of packet transmission in the network. However, slight increase in packet transmission time has been observed which is acceptable considering the improvement in quality of data being received. Present approach has been implemented, however its comparison with other existing approaches is still left as future work.

References
  1. Gupta K., Singh A., Singh R., Mukherjee S. 2015. An Improved Cluster Head Selection Algorithm for Mobile Wireless Sensor Networks. Journal of Network Communications and Emerging Technologies.
  2. Anitha, R.U., Kamalakkannan, P.  2013. Energy efficient cluster head selection algorithm in mobile wireless sensor networks, In Proceeding of International Conference on Computer Communication and Informatics (ICCCI).
  3. Gupta, D. , Verma, R., 2014. An enhanced cluster-head selection scheme for distributed nheterogeneous wireless sensor network. I proceedings of International Conference on Advances in Computing, Communications and Informatics (ICACCI).
  4. Reinhardt A., Morar O., Santiniy S., Z¨oller S. and Steinmetz R.. 2012. CBFR: Bloom Filter Routing with Gradual Forgetting for Tree-structured Wireless Sensor Networks with Mobile Nodes In Proceedings of 13th International Symposium of World of Wireless, Mobile and Multimedia Networks (WoWMoM).
  5. Hanselmann T., Zhangy Y., Morelande M., MohdIfranMd Nor, Jonathan Wei Jen Tan, Xing-She Zhouy, Yee Wei Law. 2010. Self-Localization in Wireless Sensor Networks Using Particle Filtering with Progressive Correction. In proceedings of 5th International Conference on Communication and Networking.
  6. Ye F., Luo H., Zhang S. 2005. Statistical En-Route Filtering of Injected False Data in Sensor Networks. IEEE Journal On Selected Areas in Communications.
  7. Chang D. Fang M. 2014. Bearing-Only Maneuvering Mobile Tracking With Nonlinear Filtering Algorithms in Wireless Sensor Networks. IEEE System Journal.
  8. Thampi A. K.G, Nithya L.M. 2011. An Efficient ID-Based Scheme for Filtering Gang Injected False Data in Wireless Sensor Networks. International Journal of Advanced Research in Computer and Communication Engineering.
  9. Narayanan U., Soman A. 2013. CAFS: Cluster based Authentication scheme for Filtering False data in wireless Sensor network. International Journal of Advanced Research in Computer and Communication Engineering.
  10. Jin Shyan Lee. 2008. A Petri Net Design of Command Filters for Semiautonomous Mobile Sensor Networks. IEEE Transactions On Industrial Electronics.
  11. Liu J., Zuba M., Peng,mber Z., Cui J., Zhou S. 2014. DA-Sync: A Doppler-Assisted Time-Synchronization Scheme for Mobile Underwater Sensor Networks. IEEE Transactions On Mobile Computing.
  12. XiaohuaGe, Han Q. 2014. Distributed event-triggered H1 filtering over sensor networks with communication delays. Information Sciences Journal of Elsevier.
  13. Li Li, Xia Y. 2015. UKF-based nonlinear filtering over sensor networks with wireless fading channel. Information Sciences Journal of Elsevier.
  14. Qin F., Dai X., Mitchell J. 2013. Effective-SNR estimation for wireless sensor network using Kalman filter. Ad-hoc Network Journal of Elsevier.
  15. Hur H., Ahn H. 2012. Discrete-Time H∞ Filtering for Mobile Robot Localization Using Wireless Sensor Network. IEEE Sensor Journal.
  16. Li J., Yu L., Gao H., Xiong S. 2012. Grouping-Enhanced Resilient Probabilistic En-Route Filtering of Injected False Data in WSNs. IEEE Transactions On Parallel and Distributed Systems.
  17. Blaß E., Tiede L., Zitterbart M. 2006. An Energy-Efficient and Reliable Mechanism for Data Transport in Wireless Sensor Networks. In Proceedings of International Conference on Networked Sensing Systems.
  18. Juneja D., Sharma A., Sharma A.K. 2011. A Novel Application of Extended Kalman Filter for Efficient Information Processing In Sub surfaces. International Journal of Computer Applications.
  19. Juneja D., Gupta K., Singh S. 2015. Exploiting Mobility of Agents for Data Sharing and Aggregation in a Clustered Mobile Wireless Sensor Networks. Journal of Network Communications and Emerging Technologies.
  20. T. Rappaport 1996. Wireless Communications: Principles & Practice .Englewood Cliffs, NJ: Prentice-Hall.
Index Terms

Computer Science
Information Sciences

Keywords

Data Filtering Hybrid Filtering Energy efficiency Periodic Filtering noisy data.

Powered by PhDFocusTM