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

Minimum Latency Data Aggregation in Wireless Sensor Network

by Gagandeep Kaur, Sukhwinder Singh Sran, Navjot Kaur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 134 - Number 12
Year of Publication: 2016
Authors: Gagandeep Kaur, Sukhwinder Singh Sran, Navjot Kaur
10.5120/ijca2016908056

Gagandeep Kaur, Sukhwinder Singh Sran, Navjot Kaur . Minimum Latency Data Aggregation in Wireless Sensor Network. International Journal of Computer Applications. 134, 12 ( January 2016), 30-34. DOI=10.5120/ijca2016908056

@article{ 10.5120/ijca2016908056,
author = { Gagandeep Kaur, Sukhwinder Singh Sran, Navjot Kaur },
title = { Minimum Latency Data Aggregation in Wireless Sensor Network },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 134 },
number = { 12 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 30-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume134/number12/23968-2016908056/ },
doi = { 10.5120/ijca2016908056 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:34:30.433896+05:30
%A Gagandeep Kaur
%A Sukhwinder Singh Sran
%A Navjot Kaur
%T Minimum Latency Data Aggregation in Wireless Sensor Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 134
%N 12
%P 30-34
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The wireless sensor networks are highly constrained type of network having sensor nodes with more capabilities. The sensor networks are deployed in various regions to collect the data. The critical issue of wireless Sensor Networks (WSNs) are network life and latency incurred to report data, which is the main area of research nowadays. The proposed model is using an optimized localization technique for data aggregation and consists of various regional aggregators that aggregate data to reduce the energy consumption and helps to enlarge the lifespan of cluster head in our existing scheme. The proposed model has been designed using the regional aggregators which lower the routing overhead over the transit cluster heads cum routers in the path between the target cluster head and the sink node. Hence network lifetime of sensor nodes is increased. The proposed model has been proved to be efficient in case of performance parameters of transmission delay reduced by the factor of one-third. Similarly the proposed model shows better performance in terms of network load, throughput, packet delivery ratio etc. parameters. The experimental results have proved the efficiency of the proposed model in the real time applications.

References
  1. J. Zhu, X. Hu, X. Chen, “Minimum data aggregation time problem in wireless sensor networks”, pp.133-142, IEEE, 2005.
  2. O.D. Incel, A. Ghosh, B. Krishnamachari, K. Chintalapudi, “Fast data collection in tree-based wireless sensor networks”, theoretical aspects of distributed computing in sensor networks, pp.407-445, 2008.
  3. O. Goussevskaia, T. Moscibroda, R. Wattenhofer, “Local broadcasting in the physical interference model,” in Proc. of dialm-pomc, 2008.
  4. P.J. Wan, S.C.H. Huang, L. Wang, Z. wan, X.Jia, “Minimum-latency aggregation scheduling in multihop wireless networks”, in Proc. of MobiHoc, ACM, pp.185-193, 2009.
  5. O. Goussevskaia, R. Wattenhofer, M.M. Halldorsson, E. Welzl, “Capacity of arbitrary wireless network,” in Proc. of INFOCOM, IEEE, 2009.
  6. X.Y. Li, X. Xu, S. Wang, S. Tang, G. Dai, J. Zhao,Y. Qi, “Efficient data aggregation in multi-hop wireless sensor networks under physical interference model”, pp. 353-362, IEEE, 2009.
  7. Hongxing Li, Q.S. Hua, C. Wu, “Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model”, in Proc. of Modeling, Analysis and Simulation of Wireless and Mobile Systems(MSWiM), 2010.
  8. B. Yu and J.Li, “Minimum-time aggregation scheduling in multi-sink sensor networks”,8th annual IEEE communications society conference on sensor, mesh and ad-hoc communications and networks, pp. 422-430, 2011.
  9. L. Guo, Y. Li, S.K. Prasad, “An energy-efficient distributed algorithm for minimum-latency aggregation scheduling in wireless sensor networks”, in Proc. of IEEE International Conference on Distributed Computing Systems, pp. 827-836, 2011.
  10. M. Kyung An, Nhat X. Lam, Dung T. Huynh, “Minimum latency data aggregation in the physical interference model”, in Proc. of Ad Hoc Networks, pp. 2175-2186, 2012.
  11. H. Li, C. Wu, Q. S. Hua, F. C.M. Lau, “Latency-minimizing data aggregation in wireless sensor networks under physical interference model” , in Proc. of Ad Hoc Networks, pp. 52-68, 2014.
  12. S. K. Gupta and P. Sinha, “Overview of Wireless Sensor Network: A Survey”, in Proc. of International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, 2014.
  13. M. Bhandari, S. Patil, T. Raju, “A Review on Efficient and Secure transmission of data for Cluster-Based Wireless Sensor Networks”, in Proc. of International Journal of Innovative research in Science, Engineering and Technology, Vol. 3, pp. 9328-9332 , 2014.
  14. F. Gielow , G. Jakllari , M. Nogueira , A. Santos, “Data Similarity aware dynamic node clustering in wireless sensor networks”, in Proc. of Computer Networks, pp. 29-45, 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Data Aggregation Wireless Sensor Networks Latency Clustering.

Powered by PhDFocusTM