Skip to main content

Probabilistic Data Forwarding in Wireless Sensor Networks

  • Reference work entry
  • First Online:
Encyclopedia of Algorithms
  • 65 Accesses

Years and Authors of Summarized Original Work

  • 2004; Chatzigiannakis, Dimitriou, Nikoletseas, Spirakis

Problem Definition

An important problem in wireless sensor networks is that of local detection and propagation, i.e., the local sensing of a crucial event and the energy and time efficient propagation of data reporting its realization to a control center (for a graphical presentation, see Fig. 1). This center (called the “sink”) could be some human authorities responsible of taking action upon the realization of the crucial event. More formally:

Definition 1

Assume that a single sensor, E, senses the realization of a local event\( { \mathcal{E} } \). Then the propagation problem is the following: “How can sensor P, via cooperation with the rest of the sensors in the network, efficiently propagate information reporting the realization of the event to the sink S?”

Note that this problem is in fact closely related to the more general problem of data propagation in sensor networks.

...

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 1,599.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 1,999.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. J Comput Netw 38:393–422

    Article  Google Scholar 

  2. Chatzigiannakis I, Kinalis A, Nikoletseas S (2006) Sink mobility protocols for data collection in wireless sensor networks. In: Proceedings of the 4th ACM/IEEE international workshop on mobility management and wireless access protocols (MobiWac). ACM, pp 52–59

    Google Scholar 

  3. Chatzigiannakis I, Dimitriou T, Nikoletseas S, Spirakis P (2004) A probabilistic algorithm for efficient and robust data propagation in smart dust networks. In: Proceedings of the 5th European wireless conference on mobile and wireless systems (EW 2004), pp 344–350. Also in: Ad-Hoc Netw J 4(5):621–635 (2006)

    Google Scholar 

  4. Chatzigiannakis I, Dimitriou T, Mavronicolas M, Nikoletseas S, Spirakis P (2003) A comparative study of protocols for efficient data propagation in smart dust networks. In: Proceedings of the 9th European symposium on parallel processing (EuroPar), distinguished paper. Lecture notes in computer science, vol 2790. Springer, pp 1003–1016. Also in the Parall Process Lett (PPL) J 13(4):615–627 (2003)

    Google Scholar 

  5. Chatzigiannakis I, Kinalis A, Nikoletseas S (2005) An adaptive power conservation scheme for heterogeneous wireless sensors. In: Proceedings of the 17th annual ACM symposium on parallelism in algorithms and architectures (SPAA 2005). ACM, pp 96–105. Also in: Theory Comput Syst (TOCS) J 42(1):42–72 (2008)

    Google Scholar 

  6. Estrin D, Govindan R, Heidemann J, Kumar S (1999) Next century challenges: scalable coordination in sensor networks. In: Proceedings of the 5th ACM/IEEE international conference on mobile computing (MOBICOM)

    Google Scholar 

  7. Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii international conference on system sciences (HICSS)

    Google Scholar 

  8. Intanagonwiwat C, Govindan R, Estrin D (2000) Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Proceedings of the 6th ACM/IEEE international conference on mobile computing (MOBICOM)

    Google Scholar 

  9. Kahn JM, Katz RH, Pister KSJ (1999) Next century challenges: mobile networking for smart dust. In: Proceedings of the 5th ACM/IEEE international conference on mobile computing, pp 271–278

    Google Scholar 

  10. Leone P, Rolim J, Nikoletseas S (2005) An adaptive blind algorithm for energy balanced data propagation in wireless sensor networks. In: Proceedings of the IEEE international conference on distributed computing in sensor networks (DCOSS). Lecture notes in computer science (LNCS), vol 3267. Springer, pp 35–48

    Google Scholar 

  11. Luo J, Hubaux J-P (2005) Joint mobility and routing for lifetime elongation in wireless networks. In: Proceedings of the 24th INFOCOM

    Google Scholar 

  12. Nikoletseas S, Chatzigiannakis I, Antoniou A, Efthymiou C, Kinalis A, Mylonas G (2004) Energy efficient protocols for sensing multiple events in smart dust networks. In: Proceedings of the 37th annual ACM/IEEE simulation symposium (ANSS'04). IEEE Computer Society Press, pp 15–24

    Google Scholar 

  13. Triantafillou P, Ntarmos N, Nikoletseas S, Spirakis P (2003) NanoPeer networks and P2P worlds. In: Proceedings of the 3rd IEEE international conference on peer-to-peer computing (P2P 2003), pp 40–46

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this entry

Cite this entry

Nikoletseas, S. (2016). Probabilistic Data Forwarding in Wireless Sensor Networks. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_301

Download citation

Publish with us

Policies and ethics