Real Time Approach for Data Placement Using Distributed Cellular Framework Based Clustering for Large Scale Sensor Networks

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 129)


Any large scale real world Wireless Sensor Network (WSN) based application would require the sensor network to provide more features besides the energy consumption. The issues of the scalability, fault tolerance, efficient data placement as well as retrieval and real time communication are all key requirements besides energy efficiency. The existing real time approaches are not energy efficient. Moreover they are only suitable for specific types of applications and do not work well in large scale applications therefore there is a need for an effective and efficient approach which can work in any type of situation and application. In this paper, we have proposed a distributed cellular approach for our proposed real time data placement model for WSNs. It is assumed that the sensor nodes are time synchronized and aware of their locations in their deployment area. The usage of Action and Relay Stations (ARS) has been proposed for data dissemination and action in the wireless sensor network.


Large scale sensor Network Realtime Clustering Cellular Base Station (BS) Action and Relay Stations (ARS) 


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  1. 1.
    Bojkovic, Z., Bakmaz, B.: A Survey on Wireless Sensor Networks Deployment. WSEAS Transactions on Comm. 7(12), 1172–1181 (2008)Google Scholar
  2. 2.
    Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications 1(4), 660–670 (2002)CrossRefGoogle Scholar
  3. 3.
    Stankovic, J., Abdelzaher, T., Lu, C., Sha, L., Hou, J.: Real time communication and coordination in embedded sensor networks. Proceedings of the IEEE 91(7), 1002–1022 (2003)CrossRefGoogle Scholar
  4. 4.
    Lindsey, S., Raghavendra, C.S.: PEGASIS: Power-Efficient Gathering in Sensor Information System. In: IEEE Aerospace Conference Proceedings 2002, vol. 3, pp. 1125–1130 (2002)Google Scholar
  5. 5.
    Younis, O., Fahmy, S.: HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks. IEEE Trans. on Mobile Computing 3(4), 366–379 (2004)CrossRefGoogle Scholar
  6. 6.
    Zhan, A.-D., Xu, T.-Y., Chen, G.-H., Ye, B.-L., Lu, S.-L.: A Survey on Real-time Routing Protocols for Wireless Sensor Networks. In: First China-Korea WSN International Workshop (CKWSN 2008), October 12-15 (2008)Google Scholar
  7. 7.
    Lu, C., Blum, B.M., Abdelzaher, T.F., Stankovic, J.A., He, T.: RAP: A Real-Time Communication Architecture for Large-Scale Wireless Sensor Networks. In: Eighth IEEE Real-Time and Embedded Technology and Applications Symposium, pp. 55–66 (2002)Google Scholar
  8. 8.
    He, T., Stankovic, J.A., Lu, C., Abdelzaher, T.: SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks. In: Proceedings of 23rd International Conference on Distributed Computing Systems, Providence, Rhode Island, USA, May 19-22, pp. 46–55 (2003)Google Scholar
  9. 9.
    Felemban, E., Lee, C.-G., Ekici, E., Boder, R., Vural, S.: Probabilistic QoS Guarantee in Reliability and Timeliness Domains in Wireless Sensor Networks. In: Proceedings of IEEE INFOCOM 2005, March 13-17, vol. 4, pp. 2646–2657 (2005)Google Scholar
  10. 10.
    Yuan, L., Cheng, W., Du, X.: An energy-efficient real-time routing protocol for sensor networks. Computer Communications 30(10), 2274–2283 (2007)CrossRefGoogle Scholar
  11. 11.
    Akyildiz, I.F., Kasimoglu, I.H.: Wireless sensor and actor networks: Research challenges. Ad Hoc Networks 2(4), 351–367 (2004)CrossRefGoogle Scholar
  12. 12.
    Gupta, S., Dave, M.: Distributed Real Time Architecture for Data Placement in Wireless Sensor Networks. Journal of Computer Science 5(12), 1060–1067 (2009)CrossRefGoogle Scholar
  13. 13.
    Ganesan, D., Estrin, D., Heidemann, J.: DIMENSIONS: Why do we need a new data handling architecture for sensor networks? In: Proceedings of the ACM HotNets, Princeton, NJ, USA, pp. 143–148 (October 2002)Google Scholar
  14. 14.
    Heidemann, J., Silva, F., Intanagonwiwat, C., Govindan, R., Estrin, D., Ganesan, D.: Building efficient wireless sensor networks with low-level naming. In: Proceedings of the Eighteenth ACM Symposium on Operating Systems Principles, Banff, Alberta, Canada, pp. 146–159 (2001)Google Scholar
  15. 15.
    Intanagonwiwat, C., Govindan, R., Estrin, D., Heidemann, J., Silva, F.: Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking 11(1), 2–16 (2003)CrossRefGoogle Scholar
  16. 16.
    Shenker, S., Ratnasamy, S., Karp, B., Govindan, R., Estrin, D.: Data-Centric Storage in Sensornets. ACM SIGCOMM Computer Communication Review 33(1), 137–142 (2003)CrossRefGoogle Scholar
  17. 17.
    Shah, R.C., Rabaey, J.M.: Energy Aware Routing for Low Energy Ad Hoc Sensor Networks. In: Proceedings of the IEEE Wireless Communications and Networking Conference, Orlando, pp. 350–355 (March 2002)Google Scholar
  18. 18.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, Maui, Hawaii, January 4-7, 2000, vol. 8, p. 8020 (2000)Google Scholar

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© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Autonomous body of Deptt. of I.T.Govt. of IndiaDoeacc SocietyChandigarhIndia
  2. 2.Deptt. of Computer Engg.National Institute of TechnologyKurukshetraIndia

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