Skip to main content

Advertisement

Log in

Wheel Based Event Triggered Data Aggregation and Routing in Wireless Sensor Networks: Agent Based Approach

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Event triggered data aggregation and routing minimizes the amount of energy and bandwidth required to transmit the data from the event affected area. This paper proposes a Wheel based Event Triggered data aggregation and routing (WETdar) scheme in Wireless Sensor Networks (WSNs) by employing a set of static and mobile agents. A wheel with spokes is constructed by WSN nodes around an event node (a sensor node where an event occurs). Gathering and aggregation of the information is performed along the spokes of a wheel in Spoke Aggregator (SA) nodes and sent to an event node, which routes to a sink node. Spoke generation and identification of SA nodes along the spokes is performed by using a mobile agent, based on parameters such as Euclidean distance, residual energy, spoke angle and connectivity. Mobile agent and its clones discover multiple paths to a sink node from an event node. The scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach. The performance parameters analyzed are number of SAs, SA selection time, aggregation time, aggregation energy, energy consumption, number of isolated nodes and network life time. We observed that proposed scheme outperforms as compared to the existing aggregation scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Akyildiz I. F., Vuran M. C., Akan O. B., Su W. (2004) Wireless sensor networks: A survey revisited. Elsevier Computer Netorks 45(3): 245–261

    Article  MATH  Google Scholar 

  2. Vieira, M. A. M., da Silva, D. C., Jr., Coelho, C. N., & da Mata, J. M. (2003). Survey on wireless sensor network devices. In IEEE proceedings of conference ETFA 03 (Vol. 1, pp. 537–54).

  3. Younis M., Akkaya K. (2008) Strategies and techniques for node placement in wireless sensor networks: A survey. Elsevier Ad Hoc Networks 4: 621–655

    Article  Google Scholar 

  4. Heinzelman W. B., Chandrakasan A. P., Balakrishnan H. (2002) application specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications 1(4): 660–670

    Article  Google Scholar 

  5. Chong C. Y., Kumar S. P. (2003) Sensor networks: Evolution, opportunities, and challenges. Proceedings of the IEEE 91(8): 1247–1256

    Article  Google Scholar 

  6. Gupta P., Kumar P. R. (2000) The capacity of wireless networks. IEEE Transactions on Information Theory 46(2): 388–404

    Article  MathSciNet  MATH  Google Scholar 

  7. Nakamura E. F., Loureiro A. A. F. (2007) Information fusion in wireless sensor networks. ACM Computing Surveys 39(3): 41–48

    Article  Google Scholar 

  8. Fasolo E., Rossi M., Widmer J., Zorzi M. (2007) In-network aggregation techniques for wireless sensor networks: A survey. IEEE Wireless Communication Magazine 14(2): 70–87

    Article  Google Scholar 

  9. Al-Karaki J. N., Ul-Mustafa R., Kamal A. E. (2009) Data aggregation and routing in wireless sensor networks: Optimal and heuristic algorithms. Elsevier Computer Networks 53(7): 945–960

    Article  MATH  Google Scholar 

  10. Yuanzhu C., Liestman A. L., Liu J. (2006) A hierarchical energy-efficient framework for data aggregation in wireless sensor networks. IEEE Transactions on Vehicular Technology 55(3): 789–796

    Article  Google Scholar 

  11. Tan H.O., Korpeoglu I., Stojmenovic I. (2011) Computing localized power-efficient data aggregation trees for sensor networks. IEEE Transactions on Parallel and Distributed Computing Systems 22(3): 489–500

    Article  Google Scholar 

  12. Huad C., Yum T.-S. P. (2008) Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks. IEEE/ACM Transactions on Networking 16(4): 892–903

    Article  Google Scholar 

  13. Sha, K., Gehlot, J., Greve, R. (2012) Multipath routing techniques in wireless sensor networks: A survey. Springer Journal of Wireless Personal Communication. doi:10.1007/s11277-012-0723-2 (published online June 30, 2012).

  14. Jiang H., Jin S., Wang C. (2010) Parameter-based data aggregation for statistical information extraction in wireless sensor networks. IEEE Transactions on Vehicular Technology 59(8): 3992–4001

    Article  Google Scholar 

  15. Cayirci E. (2003) Data aggregation and dilution by modulus addressing in wireless sensor networks. IEEE Communications Letters 7(8): 355–357

    Article  Google Scholar 

  16. Fan K.-W., Liu S., Sinha P. (2007) Structure free data aggregation in sensor networks. IEEE Transactions on Mobile Computing 6(8): 929–942

    Article  Google Scholar 

  17. Bouabdallah F., Bouabdallah N. (2008) The tradeoff between maximizing the sensor network lifetime and the fastest way to report reliably an event using reporting nodes’ selection. Elsevier Computer Communications 31(9): 1763–1777

    Article  Google Scholar 

  18. Galluccio L., Palazzo S., Campbell A. T. (2009) Modeling and designing efficient data aggregation in wireless sensor networks under entropy and energy bounds. Springer Wireless Information Networks 16: 175–183

    Article  Google Scholar 

  19. Kalpakis K., Dasgupta K., Namjoshi P. (2003) Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks. Elsevier Computer Networks 42: 697–716

    Article  MATH  Google Scholar 

  20. Wenz, M., & Wom, H. (2006). Event-based production rules for data aggregation in wireless sensor networks. In Proceedings of IEEE international conference on multisensor fusion and integration for intelligent systems, Heidelberg, Germany, September 3–6, 2006.

  21. Guo W., Xiong N., Vasilakos A. V., Chen G., Cheng H. (2011) Multi-source temporal data aggregation in wireless sensor networks. Springer Wireless personal communications 56(3): 359–379

    Article  Google Scholar 

  22. Park S.-J., Sivakumar R. (2008) Energy efficient correlated data aggregation for wireless sensor networks. Taylor and Francis Distributed Sensor Networks 4: 12–26

    Google Scholar 

  23. Wang N.-C., Huang Y.-F., Chen J.-S., Yeh P.-C. (2007) Energy-aware data aggregation for grid-based wireless sensor networks with a mobile sink. Springer Wireless Personal Communications 43(4): 1539–1551

    Article  Google Scholar 

  24. Selvakennedy S., Sinnappan S. (2007) An adaptive data dissemination strategy for wireless sensor networks. Taylor and Francis Distributed Sensor Networks 3(1): 23–40

    Article  Google Scholar 

  25. Ferng H.-W., Tendean R., Kurniawan A. (2012) Energy-efficient routing protocol for wireless sensor networks with static clustering and dynamic structure. Springer Journal of Wireless Personal Communication 65: 347–367

    Article  Google Scholar 

  26. Gupta H., Navda V., Das S., Chowdhary V. (2008) Efficient gathering of correlated data in sensor networks. ACM Transactions on Sensor Networks 4(1): 2–16

    Article  Google Scholar 

  27. Seung, J. B., & de Veciana, G. (2007). Spatial model for energy burden balancing and data fusion in sensor networks detecting bursty events. IEEE Transactions on Information Theory 53(10), 3615–3628.

    Google Scholar 

  28. Chen, Y., Shu, J., Liu, H., Liu, L., & Gong, J. (2009). MRDWA: Multi-role dynamic weighting aggregation algorithm in event driven wireless sensor networks. In Proceedings of fifth international conference on information assurance and security, pp. 311–314.

  29. Balasubramanian, G., & Chakrabarti, S. (2008). Modelling information generation in event-driven sensor networks. In Proceedings of IEEE/ACS conference on computer systems and applications, AICCSA 08, pp. 820–823.

  30. Sutagundar, A., Manvi, S. (2011). Sink driven axes based data aggregation in wireless sensor network. In Proceedings of 24th international conference on computers and their applications in industry and engineering (CAINE-2011), November 16–18, 2011.

  31. Vizireanu D. N. (2007) Generalizations of binary morphological shape decomposition. Journal of Electronic Imaging 16(1): 1–6

    Article  Google Scholar 

  32. Vizireanu D. N. (2008) Morphological shape decomposition interframe interpolation method. Journal of Electronic Imaging 18(2): 1–5

    Google Scholar 

  33. Udrea R.M., Vizireanu D.N. (2008) Quantized multiple sinusoids signal estimation algorithm. Journal of Instrumentation 3(2): 1–7

    Article  Google Scholar 

  34. Vizireanu D. N., Halunga S. V. (2012) Analytical formula for three points sinusoidal signals amplitude estimation errors. International Journal of Electronics 99(1): 149–151

    Article  Google Scholar 

  35. Funfrocken, S., & Mattern, F. Mobile agents as architectural concept for Internet-based distributed applications: The WASP project approach. http://citeseer.nj.nec.com/14154.html.

  36. Schmidt S., & Scott A. QoS support within active LARA++ routers. http://citeseer.nj.nec.com/schmid00qos.html.

  37. Franklin, S., & Graser, A. (1996). Is it an agent or just a program : A taxonomy for autonomous agents. In Proceedings international workshop on agent theories, architectures and languages. http://citeseer.nj.nec.com/32780.html.

  38. Jennings N. (1997) Developing agent-based systems. IEE Software Engineering 44(1): 1–2

    Article  Google Scholar 

  39. Manvi S. S., Venkataram P. (2004) Applications of agent technology in communications: A review. Computer Communications 27(15): 1493–1508

    Article  Google Scholar 

  40. Ramadan, R. A. (2009). Agent based multipath routing in wireless sensor networks. In proceedings of IEEE symposium oné1intelligent agents IA 09, pp. 63–69.

  41. Olfati-Saber, R. (2007). Distributed Kalman filtering for sensor networks. In Proceedings of the 46th IEEE conference on decision and control.

  42. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy efficient communication protocol for wireless microsensor networks. In Proceedings of the IEEE Hawaii international conference on system sciences.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Sutagundar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sutagundar, A.V., Manvi, S.S. Wheel Based Event Triggered Data Aggregation and Routing in Wireless Sensor Networks: Agent Based Approach. Wireless Pers Commun 71, 491–517 (2013). https://doi.org/10.1007/s11277-012-0825-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-012-0825-x

Keywords