Skip to main content

Advertisement

SpringerLink
Log in

Optimizing routing based on congestion control for wireless sensor networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Along with the increasing demands for the applications running on the wireless sensor network (WSN), energy consumption and congestion become two main problems to be resolved urgently. However, in most scenes, these two problems aren’t considered simultaneously. To address this issue, in this paper a solution that sufficiently maintains energy efficiency and congestion control for energy-harvesting WSNs is presented. We first construct a queuing network model to detect the congestion degree of nodes. Then with the help of the principle of flow rate in hydraulics, an optimizing routing algorithm based on congestion control (CCOR) is proposed. The CCOR algorithm is designed by constructing two functions named link gradient and traffic radius based on node locations and service rate of packets. Finally, the route selection probabilities for each path are allocated according to the link flow rates. The simulation results show that the proposed solution significantly decreases the packet loss rate and maintains high energy efficiency under different traffic load.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

References

  1. Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., & Leung, V. C. M. (2010). Body area networks: A survey. Mobile Networks and Applications, 16(2), 171–193.

    Article  Google Scholar 

  2. Liu, J., Wang, Q., Wan, J., X, J., & Zeng, B. (2013). Towards key issues of disaster aid based on wireless body area networks. KSII Transactions on Internet and Information Systems, 7(5), 1014–1035.

    Article  Google Scholar 

  3. Xiang, L., Luo, J., & Vasilakos, A. (2011).Compressed data aggregation for energy efficient wireless sensor networks. In Proceedings of the 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON’11).

  4. Vasilakos, A. V., Li, Z., Simon, G., & You, W. (2015). Information centric network: Research challenges and opportunities. Journal of Network and Computer Applications, 52, 1–10.

    Article  Google Scholar 

  5. Wu, Y., & Liu, W. (2013). Routing protocol based on genetic algorithm for energy harvesting-wireless sensor networks. Wireless Sensor Systems, 3(2), 112–118.

    Article  Google Scholar 

  6. Li, M., Li, Z., & Vasilakos, A. V. (2013). A Survey on topology control in wireless sensor networks, taxonomy, comparative study, and open issues. Proceedings of the IEEE, 101(12), 2538–2557.

    Article  Google Scholar 

  7. Zeng, Y., Xiang, K., Li, D., & Vasilakos, A. V. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  8. Xu, X., Ansari, R., Khokhar, A., & Vasilakos, A. V. (2015). Hierarchical data aggregation using compressive sensing in WSNs. ACM Transactions on Sensor Networks (TOSN), 11(3), 294–312.

  9. Sengupta, S., Das, S., Nasir, M., Vasilakos, A. V., & Pedrycz, W. (2012). An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Review, 42(6), 1093–1102.

    Article  Google Scholar 

  10. Wang, X., Vasilakos, A. V., Chen, M., Liu, Y., & Kwon, T. T. (2012). A survey of green mobile networks: Opportunities and challenges. Mobile Networks and Applications, 17(1), 4–20.

    Article  Google Scholar 

  11. Han, K., Luo, J., Liu, Y., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.

    Article  Google Scholar 

  12. Youssef, M., Ibrahim, M., Abdelatif, M., Chen, L., & Vasilakos, A. V. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys and Tutorials, 16(1), 92–109.

    Article  Google Scholar 

  13. Dvir, A., & Vasilakos, A. V. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.

    Google Scholar 

  14. Chen, M., Wan, J., Gonzalez, S., Liao, X., & Leung, V. C. M. (2014). A survey of recent developments in home M2M networks. IEEE Communications Surveys and Tutorials, 16(1), 98–114.

    Article  Google Scholar 

  15. Sheng, Z., Yang, S., Yu, Y., Vasilakos, A. V., McCann, J. A., & Leung, K. K. (2013). A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.

    Article  Google Scholar 

  16. Busch, C., Kannan, R., & Vasilakos, A. V. (2012). Approximating congestion+ dilation in networks via “quality of routing” games. IEEE Trans. Computers, 61(9), 1270–1283.

    Article  MathSciNet  Google Scholar 

  17. Zawodniok, M., & Jagannathan, S. (2007). Predictive congestion control protocol for wireless sensor networks. IEEE Transactions on Wireless Communications, 6(11), 3955–3963.

    Article  Google Scholar 

  18. Yaghmaee, M. H., & Adjeroh, D. A. (2009). Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Computer Networks, 53(11), 1798–1811.

    Article  MATH  Google Scholar 

  19. Levis, P., Lee, N., Welsh, M., & Culler, D. (2003). TOSSIM: Accurate and scalable simulation of entire Tinyos applications. In Proceedings of the 1st international conference on Embedded networked sensor systems (SenSys’03).

  20. Ren, F., He, T., Das, S., & Lin, C. (2011). Traffic-aware dynamic routing to alleviate congestion in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22(9), 1585–1599.

    Article  Google Scholar 

  21. Yao, Y., Cao, Q., & Vasilakos, A. V. (2015). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks. IEEE/ACM Transactions on Networking, 23(3), 810–823.

    Article  Google Scholar 

  22. Yen, Y. S., Chao, H. C., Chang, R. S., & Vasilakos, A. V. (2011). Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11–12), 2238–2250.

    Article  Google Scholar 

  23. Song, Y., Liu, L., Ma, H., & Vasilakos, A. V. (2014). A Biology-based algorithm to minimal exposure problem of wireless sensor networks. IEEE Transactions on Network and Service Management, 11(3), 417–430.

    Article  Google Scholar 

  24. Meng, T., Wu, F., Yang, Z., Chen, G., & Vasilakos, A. V. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE Transactions on Computers, PP(99), 1–13.

    Article  Google Scholar 

  25. Li, P., Guo, S., & Vasilakos, A.V. (2012). CodePipe: An opportunistic feeding and routing protocol for reliable multicast with pipelined network coding. In Proceedings of IEEE INFOCOM.

  26. Li, P., Guo, S., Yu, S., & Vasilakos, A. V. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.

    Article  Google Scholar 

  27. Wu, J., & Wang, Y. (2014). Hypercube-based multipath social feature routing in human contact networks. IEEE Transactions on Computers, 63(2), 383–396.

    Article  MathSciNet  Google Scholar 

  28. Azad, S., Casari, P., & Zorzi, M. (2014). Multipath routing with limited cross-path interference in underwater networks. IEEE Wireless Communications Letters, 3(5), 465–468.

    Article  Google Scholar 

  29. Han, D., & Chung, J. M. (2014). Self-similar traffic end-to-end delay minimization multipath routing algorithm. IEEE Wireless Communications Letters, 18(12), 2121–2124.

    Article  Google Scholar 

  30. Xiao, Y., Peng, M., Gibson, J., Xie, G. G., Du, D. Z., & Vasilakos, A. V. (2012). Tight performance bounds of multihop fair access for mac protocols in wireless sensor networks and underwater sensor networks. IEEE Transactions on Mobile Computing, 11(10), 1538–1554.

    Article  Google Scholar 

  31. Chilamkurti, N., Zeadally, S., Vasilakos, A., & Sharma, V. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensor, 29(2), 334–342.

    Google Scholar 

  32. Liu, Y., Xiong, N., Zhao, Y., Vasilakos, A. V., & Gao, J. (2009). Multi-layer clustering routing algorithm for wireless vehicular sensor networks. IET Communications, 4(7), 810–816.

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  34. Bisnik, N., & Abouzeid, A. (2009). Queuing network models for delay analysis of multihop wireless ad hoc networks. Ad Hoc Networks, 7(1), 79–97.

    Article  Google Scholar 

  35. Burno, R., Conti, M., & Pinizzotto, A. (2009). A queuing modeling approach for load-aware route selection in heterogeneous mesh networks. IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks & Workshops (WoWMoM 2009).

Download references

Acknowledgments

This work was supported by the National High Technology Research and Development of China (no. 2014AA01A701), Beijing Natural Science Foundation (4142049) and Fundamental Research Funds for the Central Universities (2015XS07).

Author information

Authors and Affiliations

  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China

    Wei Ding, Liangrui Tang & Shiyu Ji

Authors
  1. Wei Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liangrui Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shiyu Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Ding.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, W., Tang, L. & Ji, S. Optimizing routing based on congestion control for wireless sensor networks. Wireless Netw 22, 915–925 (2016). https://doi.org/10.1007/s11276-015-1016-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-1016-y

Keywords

Search

Navigation