Skip to main content
Log in

A Queuing Theory-Enabled Dynamic Bandwidth Allocation Algorithm for a Wired-Wireless Converged Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Multi-sink wireless sensor networks (WSNs) are being increasingly deployed in an ever-widening range of application scenarios, especially as they are reliable and exhibit low power consumption. Providing a backhaul for WSN traffic has become an important issue because the sensor data must usually be sent to the Internet or the core network. Passive optical networks (PONs) represent one next-generation access network technology which is appropriate for such a backhaul, however existing research appears to have concentrated on either WSN performance or PON performance, without considering the overall performance of both networks converged together. This paper proposes a new architecture which converges multi-sink WSNs and PONs, then provides a novel queuing-theory analysis of the converged network performance. Results from this analytical model are then used to motivate a new a DBA algorithm which optimizes grant size allocation. Numerical results show that this algorithm outperforms existing proposals when minimizing the system queue length in the converged network, while providing shorter end-to-end packet delay and higher throughput. We believe that this first resource allocation algorithm which considers the performance of both networks as one converged unit.

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Akyildiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. Communications Magazine, IEEE, 40(8), 102–114.

    Article  Google Scholar 

  2. Akyildiz, I., Melodia, T., & Chowdhury, K. (2008). Wireless multimedia sensor networks: Applications and testbeds. Proceedings of the IEEE, 96(10), 1588–1605.

    Article  Google Scholar 

  3. Akyildiz, I., Melodia, T., & Chowdury, K. (2007). Wireless multimedia sensor networks: A survey. Wireless Communications, IEEE, 14(6), 32–39.

    Article  Google Scholar 

  4. Bekmezci, I., & Alagoz, F. (2008). Energy efficient, delay sensitive, fault tolerant wireless sensor network for military monitoring. In Sensors applications symposium, 2008. SAS 2008. IEEE (pp. 172–177).

  5. Chen, S.-L., Lee, H.-Y., Chen, C.-A., Huang, H.-Y., & Luo, C.-H. (2009). Wireless body sensor network with adaptive low-power design for biometrics and healthcare applications. Systems Journal, IEEE, 3(4), 398–409.

    Article  Google Scholar 

  6. Holman, R., Stanley, J., & Ozkan-Haller, T. (2003). Applying video sensor networks to nearshore environment monitoring. Pervasive Computing, IEEE, 2(4), 14–21.

    Article  Google Scholar 

  7. Jiang, H., Chen, L., Wu, J., Chen, S., & Leung, H. (2009). A reliable and high-bandwidth multihop wireless sensor network for mine tunnel monitoring. Sensors Journal, IEEE, 9(11), 1511–1517.

    Article  Google Scholar 

  8. Kazovsky, L., Shaw, W.-T., Gutierrez, D., Cheng, N., & Wong, S.-W. (2007). Next-generation optical access networks. Journal of Lightwave Technology, 25(11), 3428–3442.

    Article  Google Scholar 

  9. Mcgarry, M., Reisslein, M., & Maier, M. (2008). Ethernet passive optical network architectures and dynamic bandwidth allocation algorithms. Communications Surveys Tutorials, IEEE, 10(3), 46–60.

    Article  Google Scholar 

  10. Kramer, G., Mukherjee, B., & Pesavento, G. (2002). Ipact a dynamic protocol for an ethernet pon (epon). Communications Magazine, IEEE, 40(2), 74–80.

    Article  Google Scholar 

  11. Holmberg, T., (2006). Analysis of epons under the static priority scheduling scheme with fixed transmission times. In Next generation internet design and engineering, 2006. NGI ’06. 2006 2nd Conference on, 0–0, pp. 8-199.

  12. Bhatia, S., Garbuzov, D., & Bartos, R. (2006, June). Analysis of the gated ipact scheme for epons. In Communications, 2006. ICC ’06. IEEE international conference on (Vol. 6, pp. 2693–2698).

  13. Bharati, S., & Saengudomlert, P. (2009). Simple derivation of mean packet delay for gated service in epons. In Electrical engineering/electronics, computer, telecommunications and information technology, 2009. ECTI-CON 2009. 6th International conference on (Vol. 2, pp. 972–975).

  14. Roy, A., Mitra, A., Khan, A., Nasipuri, M., & Saha, D., (2008). Lsdc a lossless approach to lifetime maximization in wireless sensor networks. In Sensors applications symposium, 2008. SAS 2008. IEEE (pp. 166–171).

  15. Le, N. T., Choi, S. W., & Jang, Y. M. (2010, June). Approximate queuing analysis for ieee 802.15.4 sensor network. In Ubiquitous and future networks (ICUFN), 2010 2nd international conference on, June 2010 (pp. 193–198).

  16. He, L., Zhuang, Y., Pan, J., & Xu, J. (2010). Evaluating on-demand data collection with mobile elements in wireless sensor networks. In Vehicular technology conference Fall (VTC 2010-Fall), 2010 IEEE 72nd (pp. 1–5).

  17. Jiang, F.-C., Huang, D.-C., Yang, C.-T., & Wang, K.-H. (2010, August). Mitigation techniques for the energy hole problem in sensor networks using n-policy m/g/1 queuing models. In Frontier computing theory, technologies and applications, 2010 IET international conference on, August 2010 (pp. 281–286).

  18. Frank Aurzada, M. H. M. M., Scheutzow, M., & Reisslein, M. (2008). Delay analysis of ethernet passive optical networks with gated service. Journal of Optical Networking, 7(1), 25–41.

    Article  Google Scholar 

  19. Bart Lannoo, D. C. M. P. M. G., Verslegers, L., & Demeester, P. (2007). Analytical model for the ipact dynamic bandwidth allocation algorithm for epons. Journal of Optical Networking, 6(6), 667–688.

    Google Scholar 

  20. Bharati, S., & Saengudomlert, P. (2010). Analysis of mean packet delay for dynamic bandwidth allocation algorithms in epons. Journal of Lightwave Technology, 28(23), 3454–3462.

    Google Scholar 

  21. Yang, K., Ou, S., Guild, K., & Chen, H.-H. (2009). Convergence of ethernet pon and ieee 802.16 broadband access networks and its qos-aware dynamic bandwidth allocation scheme. IEEE Journal on Selected Areas in Communications, 27(2), 101–116.

    Article  Google Scholar 

  22. Zheng, Z., Wang, J., & Wang, X. (2009, December). Onu placement in fiber-wireless (fiwi) networks considering peer-to-peer communications. In Global telecommunications conference, 2009. GLOBECOM 2009. IEEE, 30 2009–Dec 4 2009 (pp. 1–7).

  23. Wang, Z., Kravtsov, K., Chang, J., & Prucnal, P. (2011). Sensor data transmission overlay on gigabit passive optical networks. IEEE/OSA Journal of Optical Communications and Networking, 3(7), 553–558.

    Article  Google Scholar 

  24. Wang, Z., Yang, K., & Hunter, D. (2011, October). Modelling and analysis of convergence of wireless sensor network and passive optical network using queueing theory. In Wireless and mobile computing, networking and communications (WiMob), 2011 IEEE 7th international conference on, Oct 2011 (pp. 37–42).

  25. Wang, Z., Yang, K., & Hunter, D. (2012, June). A dynamic bandwidth allocation algorithm for a multi-sink wireless sensor network converged with a passive optical network. In Ubiquitous computing and communications, 2012 IEEE 11th international conference on, June 2012 (pp. 1548–1554).

  26. Hock, N. (1997). Queuing modelling fundamentals. Singapore: Nanyang Technological University.

    Google Scholar 

  27. Yen, C.-M., Chang, C.-J., Ren, F.-C., & Lai, J.-A. (2009). Dynamic priority resource allocation for uplinks in ieee 802.16 wireless communication systems. IEEE Transactions on Vehicular Technology, 58(8), 4587–4597.

    Article  Google Scholar 

  28. Raza, I., Chaudhry, S., Hussain, S., Abid, S., & Raza, H. (2012). Optimised priority assignment mechanism for biomedical wireless sensor networks. Wireless Sensor Systems, IET, 2(2), 92–102.

    Article  Google Scholar 

  29. de A Lima, G., & Burns, A. (2003). An optimal fixed-priority assignment algorithm for supporting fault-tolerant hard real-time systems. IEEE Transactions on Computers, 52(10), 1332–1346.

    Article  Google Scholar 

  30. Maruyama, K., & Tang, D. T. (1977). Discrete link capacity and priority assignments in communication networks. IBM Journal of Research and Development, 21(3), 254–263.

    Article  MATH  Google Scholar 

  31. Kramer, G. (2005). Ethernet passive optical networks. In McGraw-Hill communications engineering series.

  32. Chen, B. (2005). Optimization theory and algorithms. Beijing, China: Tsinghua University Press.

Download references

Acknowledgments

The work in this paper was partly funded by EU FP7 Project EVANS (GA-2010-269323) and UK EPSRC Project DANCER (EP/K002643/1). Zhenfei Wang thanks Vasileios Iliopoulos, a PhD student in the Mathematical Sciences Department of the University of Essex, for valuable discussions on the work in this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhenfei Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, Z., Yang, K., Hunter, D.K. et al. A Queuing Theory-Enabled Dynamic Bandwidth Allocation Algorithm for a Wired-Wireless Converged Network. Wireless Pers Commun 72, 1373–1397 (2013). https://doi.org/10.1007/s11277-013-1084-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-013-1084-1

Keywords

Navigation