CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 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

Evaluation and Comparative Study of Structure Free Aggregation Techniques for Duty Cycled Wireless Sensor Networks

by Sukhwinder Singh Sran, Lakhwinder Kaur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 170 - Number 8
Year of Publication: 2017
Authors: Sukhwinder Singh Sran, Lakhwinder Kaur
10.5120/ijca2017914926

Sukhwinder Singh Sran, Lakhwinder Kaur . Evaluation and Comparative Study of Structure Free Aggregation Techniques for Duty Cycled Wireless Sensor Networks. International Journal of Computer Applications. 170, 8 ( Jul 2017), 1-8. DOI=10.5120/ijca2017914926

@article{ 10.5120/ijca2017914926,
author = { Sukhwinder Singh Sran, Lakhwinder Kaur },
title = { Evaluation and Comparative Study of Structure Free Aggregation Techniques for Duty Cycled Wireless Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2017 },
volume = { 170 },
number = { 8 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume170/number8/28087-2017914926/ },
doi = { 10.5120/ijca2017914926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:17:54.343554+05:30
%A Sukhwinder Singh Sran
%A Lakhwinder Kaur
%T Evaluation and Comparative Study of Structure Free Aggregation Techniques for Duty Cycled Wireless Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 170
%N 8
%P 1-8
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For delay sensitive event based applications, structure free data aggregation approach has been found to be more suitable because of the reduced structure maintenance overhead. However, in the literature, it has been observed that increasing the delay at intermediate sensor node increases aggregation and the event notification time. The objective is to investigate various structure free aggregation schemes in terms of aggregation gain, event notification time and the overall energy consumption. To achieve this objective, a comparative study of various structure free aggregation techniques is presented. First, we investigate the potential of aggregation in different structure free aggregation techniques for duty cycled sensor networks. Then the performance of the aggregation techniques is demonstrated with the help of simulations on Cooja network simulator in Contiki operating system. From the results, it has been observed that Tuned delay based aggregation scheme reduces energy consumption (upto 13%) as compared to Collect protocol. Moreover, it reduces the worst event notification time (upto 20%) in comparison to random delay based aggregation scheme.

References
  1. I. F. Akyildiz,W. Su, Y. Sankarasubramaniam, and E. Cayirci. A survey on sensor networks. IEEE Communication Magazine, 40(8):102–114, 2002.
  2. M. Buettner, G. V. Yee, E. Anderson, and B. R. Han. X-mac: a short preamble mac protocol for duty-cycled wireless sensor networks. In 4th international conference on embedded networked sensor systems (SenSys-06), pages 307 – 320, 2006.
  3. C. M. Chao and T. Y. Hsiao. Design of structure free and energy balanced data aggregation in wireless sensor networks. Journal of Network and Computer Applications, 37:229–239, 2014.
  4. K. H. Chen, J. M. Huang, and C. C. Hsiao. Chiron: an energyefficient chain-based hierarchical routing protocol in wireless sensor networks. In Proceeding of IEEE Symposium on Wireless Telecommunications (WTS-2009), pages 1–5, Prague, 2009.
  5. S. Dietzel, B. Bako, E. Schoch, and F. Kargl. A fuzzy logic based approach for structure-free aggregation in vehicular adhoc networks. In Proceeding of 6th ACM International Workshop on Vehicle Networking (VANET-09), pages 79–88, USA, 2009.
  6. M. Ding, X. Cheng, and G. Xue. Aggregation tree construction in sensor networks. In Proceeding of 58th IEEE Vehicular Technology Conference, volume 4, pages 2168–2172, USA, 2003.
  7. A. Dunkels. The ContikiMAC Radio Duty Cycling Protocol. Technical report, Swedish Institute of Computer Science, 12 2011.
  8. A. Dunkels, F. Osterlind, N. Tsiftes, and Z. He. Softwarebased on-line energy estimation for sensor nodes. In Proceedings of the 4th workshop on Embedded networked sensors (EmNets-07), pages 28–32, USA, 2007.
  9. K. W. Fan, S. Liu, and P. Sinha. Structure-free data aggregation in sensor networks. IEEE Transactions on Mobile Computing, 6(8):929–942, 2007.
  10. O. Gnawali, R. Fonseca, K. Jamieson, M. Kazandjieva, D. Moss, and P. Levis. Ctp: An efficient, robust, and reliable collection tree protocol for wireless sensor networks. ACM Transactions on Sensor Networks, 10(1):1–50, 2013.
  11. O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis. Collection tree protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (Sensys-09), pages 1–14, USA, 2009.
  12. J. Yuhui H. Junping and D. Liang. A time-based cluster-head selection algorithm for leach. In IEEE Symposium on Computers and Communications, pages 1172–1176, 2008.
  13. W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan. An application-specific protocol architecture for wireless microsensor network. IEEE Transactions on Wireless Communications, 1(4):660–670, 2002.
  14. R. Jurdak, P. Baldi, and C. V. Lopes. Adaptive low power listening for wireless sensor networks. IEEE Transactions on Mobile Computing, 6(8):988–1004, 2007.
  15. N. Kaur, S. S. Sran, and L. Kaur. Berp: Balanced energy routing protocol for routing around connectivity holes in wireless sensor networks. In IEEE International Conference on Recent Advances in Engineering and Computational Sciences (RAECS-2015), pages 1 – 6, India, 2015.
  16. P. Levis, N. Patel, D. Culler, and S. Shenker. Trickle: A selfregulating algorithm for code propagation and maintenance in wireless sensor networks. In Proceeding of International Conference on Networked Systems Design and Implementation (NSDI-04), volume 1, pages 2–2, USA, 2004.
  17. S. J. Lim and M. S. Park. Energy-efficient chain formation algorithm for data gathering in wireless sensor networks. International Journal of Distributed Sensor Networks, 2012:1–9, 2012.
  18. S. Lindsey and C. Raghavendra. Pegasis: Power efficient gathering in sensor information systems. In Proceeding 15th International Symposium on Parallel and Distributed Processing, pages 2001–2008, 2001.
  19. S. Lindsey, C. Raghavendra, and K. M. Sivalingam. Data gathering algorithms in sensor networks using energy metrics. IEEE Transactions on Parallel and Distributed Systems, 13(9):924–935, 2002.
  20. V. Loscri, G. Morabito, and S. Marano. A two levels hierarchy for low energy adaptive clustering hierarchy. In 62nd vehicular technology conference, pages 1809–1813, 2005.
  21. C. J. Merlin and W. B. Heinzelman. Schedule adaptation of low-power-listening protocols for wireless sensor networks. IEEE Transactions on Mobile Computing, 9(5):672– 685, 2009.
  22. Moteiv Corporation. Ultra low power IEEE 802.15.4 compliant wireless sensor module.
  23. E. F. Nakamura, H. A. B. F. de Oliveira, L. F. Pontello, and A. A. F. Loureiro. On demand role assignment for event-detection in sensor networks. In 11th IEEE Symposium on Computers and Communications (ISCC-06), pages 1–7, 2006.
  24. G. J. Pottie andW. J. Kaiser.Wireless integrated network sensors. Communications of the ACM, 43(5):51–58, 2000.
  25. J. Shin and C. Sun. Creec: Chain routing with even energy consumption. Journal of Communications and Networks, 13(1):17–25, 2011.
  26. S. S. Sran, L. Kaur, G. Kaur, and S. K. Sidhu. Energy aware chain based data aggregation scheme for wireless sensor network. In IEEE International Conference on Energy Systems and Applications (ICESA-2015), pages 113 – 117, India, 2015.
  27. S. S. Sran, J. Singh, and L. Kaur. Aggregation aware early event notification technique for delay sensitive applications in wireless sensor networks. International Journal of Sensor Networks, Aceepted for publication, 2017.
  28. N. Tabassum, Q. Ehsanul, K. Mamun, and Y. Urano. Cosen: A chain oriented sensor network for efficient data collection. In Proceeding of 3rd IEEE international Conference on Information Technology, New Generations: ITNG 2006, volume 4, pages 262–267, USA, 2006.
  29. H. O. Tan and I. Korpeoglu. Power efficient data gathering and aggregation in wireless sensor networks. ACM Sigmod Record, 32(4):66–71, 2003.
  30. L. A. Villas, A. Boukerche, H. A. B. F. de Oliveira, R. B. de Araujo, and A. A.F. Loureiro. A spatial correlation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Networks, 12:69 – 85, 2014.
  31. L. A. Villas, Azzedine Boukerchel, Regina Borges de Araujo, and Antonio A. F. Loureiro. Highly dynamic routing protocol for data aggregation in sensor networks. In Proceedings of the IEEE Symposium on Computers and Communications, pages 496 – 502, 2010.
  32. L. A. Villas, D. L. Guidoni, R. B. Araujo, A. Boukerche, and A. A. F. Loureiro. A scalable and dynamic data aggregation aware routing protocol for wireless sensor networks. In Proceedings of the 13th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems (MSWIM-10), pages 110 – 117, USA, 2010.
  33. H. Yousefi, M. H. Yeganeh, N. Alinaghipour, and A. Movaghar. Structure-free real-time data aggregation in wireless sensor networks. Computer Communications, 35(9):1132–1140, 2012.
  34. J. Zhang, Q. Wu, F. Ren, T. He, and C. Lin. Effective data aggregation supported by dynamic routing in wireless sensor networks. In Proceeding of IEEE Communications (ICC- 2010), pages 1 – 6, Cape Town, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Structure free aggregation Energy efficient routing Event notification time Duty cycling Aggregation Delay

Powered by PhDFocusTM