Skip to main content

Advertisement

Log in

Fair data collection in wireless sensor networks: analysis and protocol

  • Published:
annals of telecommunications - annales des télécommunications Aims and scope Submit manuscript

Abstract

In general, wireless sensor networks (WSNs) consist of many sensors which transmit data to a central node, called the sink, possibly over multiple hops. This many-to-one data routing paradigm leads to nonuniform traffic distribution for the different sensors (e.g., nodes closer to the sink transfer more traffic than those farther away). In this paper, we perform an analysis of the fairness issue by presenting a tree-based WSN and derive the throughput, delay, and energy distribution for each sensor under the fairness constraint. Based on the analysis, we design our fair data collection protocol in which each node decides its media access and packet forwarding strategies in a distributed manner. Finally, we demonstrate the effectiveness of our solution through simulations. The results for the proposed protocol show the accuracy of the analysis and show that the protocol ensures the fair delivery of packets and reduces end-to-end delay. Based on the analysis, we also quantitatively determine the energy required for each of the nodes and show that a nonuniform energy distribution can maximize the network lifetime for the WSN scenario under study.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

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

    Article  Google Scholar 

  2. Cerpa A, Elson J, Estrin D, Girod L, Hamilton M, Zhao J (2001) Habitat monitoring: application driver for wireless communications technology. In: 2001 ACM SIGCOMM workshop on data communications in Latin America and the Caribbean, San Jose, Costa Rica. URL:http://dblp.uni-trier.de/db/journals/ccr/ccr31.html#CerpaEEGHZ01

  3. Schwiebert L, Gupta SK, Weinmann J (2001) Research challenges in wireless networks of biomedical sensors. In: MobiCom ’01: Proceedings of the 7th annual international conference on Mobile computing and networking. ACM, New York, NY, USA, pp 151–165

    Chapter  Google Scholar 

  4. Biagioni ES, Bridges KW (2002) The application of remote sensor technology to assist the recovery of rare and endangered species. Int J High Perform Comput Appl 16:315–324

    Article  Google Scholar 

  5. Mainwaring A, Culler D, Polastre J, Szewczyk R, Anderson J (2002) Wireless sensor networks for habitat monitoring. In: WSNA ’02: proceedings of the 1st ACM international workshop on wireless sensor networks and applications. ACM, New York, NY, USA, pp 88–97

    Chapter  Google Scholar 

  6. Yarvis MD, Conner WS, Krishnamurthy L, Mainwaring A, Chhabra J, Elliott B (2002) Real-world experiences with an interactive ad hoc sensor network. In: Proc. of international conference on parallel processing workshops

  7. Hamilton MP, Rundel P, Graham E, Allen M, Estrin D, Hansen M, Taggart M, Askay S, Guy R, Chang K, Lam Y, del Rio VR, Yau N, Yuen E (2006) TER 0: TEOS: terrestrial ecology observing systems overview of embedded networked systems and emissary tools for instrument management and data exploration. URL:http://research.cens.ucla.edu/pls/portal/url/item/15863C8A1F3C3959E0406180528D219B

  8. Ahn GS, Hong SG, Miluzzo E, Campbell AT, Cuomo F (2006) Funneling-MAC: a localized, sink-oriented MAC for boosting fidelity in sensor networks. In: SenSys ’06: proceedings of the 4th international conference on embedded networked sensor systems. ACM, New York, NY, USA, pp 293–306

    Chapter  Google Scholar 

  9. LAN/MAN standards committee (1999) ANSI/IEEE std 802.11: wireless LAN medium access control (MAC) and physical layer (PHY) specifications. IEEE Computer Society, Los Alamitos

    Google Scholar 

  10. Liu T, Liao W (2008) Location-dependent throughput and delay in wireless mesh networks. IEEE Trans Veh Technol 57:1188–1198

    Article  Google Scholar 

  11. Ross SM (2003) Introduction to probability models (8th edn). Academic, New York

    MATH  Google Scholar 

  12. Rai V, Mahapatra RN (2005) Lifetime modeling of a sensor network. In: Design, automation and test in Europe conference and exhibition, vol 1, pp 202–203

  13. Bianchi G (2000) Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J Sel Areas Commun 18(3):535–547

    Article  Google Scholar 

  14. The Network Simulator—ns-2. http://www.isi.edu/nsnam/ns/index.html

  15. Intanagonwiwat C, Govindan R, Estrin D (2000) Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: ACM international conference on mobile computing and networking (MOBICOM’00), pp 56–67

  16. Woo A, Culler DE (2001) A transmission control scheme for media access in sensor networks. In: MobiCom ’01: proceedings of the 7th annual international conference on mobile computing and networking. ACM, New York, NY, USA, pp 221–235

    Chapter  Google Scholar 

  17. Perkins CE, Royer EM (1999) Ad-hoc on-demand distance vector routing. In: Proceedings of the 2nd IEEE workshop on mobile computing systems and applications, pp 90–100

  18. Florens C, McEliece R (2003) Packets distribution algorithms for sensor networks. In: IEEE INFOCOM

  19. Moscibroda T (2007) The worst-case capacity of wireless sensor networks. In: IPSN ’07: proceedings of the 6th international conference on information processing in sensor networks. ACM, New York, NY, USA, pp 1–10

    Chapter  Google Scholar 

  20. Chiasserini CF, Garetto M (2004) Modeling the performance of wireless sensor networks. In: IEEE infocom

  21. Chetoui Y, Bouabdallah N (2007) Adjustment mechanism for the IEEE 802.11 contention window: An efficient bandwidth sharing scheme. Comput Commun 30(13):2686–2695

    Article  Google Scholar 

  22. Nandagopal T, Kim TE, Gao X, Bharghavan V (2000) Achieving MAC layer fairness in wireless packet networks. In: MobiCom ’00: proceedings of the 6th annual international conference on mobile computing and networking. ACM, New York, NY, USA, pp 87–98

    Chapter  Google Scholar 

  23. Huang XL, Bensaou B (2001) On max-min fairness and scheduling in wireless ad-hoc networks: analytical framework and implementation. In: MobiHoc ’01: proceedings of the 2nd ACM international symposium on mobile ad hoc networking & computing. ACM, New York, NY, USA, pp 221–231

    Chapter  Google Scholar 

  24. Luo H, Cheng J, Lu S (2004) Self-coordinating localized fair queueing in wireless ad hoc networks. IEEE Trans Mob Comput 3(1):86–98

    Article  Google Scholar 

  25. Chen S, Zhang Z (2006) Localized algorithm for aggregate fairness in wireless sensor networks. In: MobiCom ’06: proceedings of the 12th annual international conference on Mobile computing and networking. ACM, New York, NY, USA, pp 274–285

    Chapter  Google Scholar 

  26. Ee CT, Bajcsy R (2004) Congestion control and fairness for many-to-one routing in sensor networks. In: ACM SenSys. ACM, New York, pp 148–161

    Chapter  Google Scholar 

  27. Rangwala S, Gummadi R, Govindan R, Psounis K (2006) Interference-aware fair rate control in wireless sensor networks. SIGCOMM Comput Commun Rev 36(4):63–74

    Article  Google Scholar 

  28. Fan KW, Zheng Z, Sinha P (2008) Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. In: SenSys ’08: proceedings of the 6th ACM conference on embedded network sensor systems. ACM, New York, NY, USA, pp 239–252

    Chapter  Google Scholar 

  29. Li S, Liao X, Peng S, Zhu P, Jiang J (2007) Credit based fairness control in wireless sensor network. In: SNPD ’07: proceedings of the eighth ACIS international conference on software engineering, artificial intelligence, networking, and parallel/distributed computing. IEEE Computer Society, Washington, DC, USA pp 817–822

    Chapter  Google Scholar 

  30. Sridharan A, Krishnamachari B (2004) Max–min fair collision-free scheduling for wireless sensor networks. In: Workshop on multihop wireless networks (MWN’04), IPCCC

  31. Sridharan A, Krishnamachari B (2009) Maximizing network utilization with max-min fairness in wireless sensor networks. Wirel Netw 15(5):585–600

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the MKE, Korea, under the ITRC support program supervised by the NIPA (NIPA-2009-(C1090-0902-0002)). Dr. Choong Seon Hong is the corresponding author.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Choong Seon Hong.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hamid, M.A., Alam, M.M., Islam, M.S. et al. Fair data collection in wireless sensor networks: analysis and protocol. Ann. Telecommun. 65, 433–446 (2010). https://doi.org/10.1007/s12243-010-0163-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12243-010-0163-5

Keywords

Navigation