Skip to main content

Advertisement

SpringerLink
Log in

Traffic-Aware and Energy-Efficient Routing Algorithm for Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The energy of wireless sensor networks (WSNs) is generally powered by limited and portable batteries. However, there are some specific scenarios where the nodes can gain energy continuously, such as the electric energy data collection, the power line monitoring and using renewable energy. Meanwhile, due to the centralized traffic pattern in WSNs, congestion occurs easily and has a negative impact on the network performance, namely, decreasing throughput and increasing energy consumption. In this paper, a solution to sufficiently maintain the energy efficiency and avoid congestion for energy-unlimited WSNs is presented. Based on the similarity between data forwarding in WSNs and water transmission in pipeline, a traffic-aware and energy-efficient routing (TER) algorithm is proposed. The TER algorithm is designed by constructing a pipeline model in terms of physical distance and traffic load. The goal of this basic approach is to force the packets to steer clear of obstacles created by congestion and eventually move toward the sink. The simulation results show that the proposed solution generates better performance in terms of the global energy consumption , timeliness and reliability as compared to the other two algorithms.

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

Similar content being viewed by others

References

  1. Uster, H., & Lin, H. (2011). Integrated topology control and routing in wireless sensor networks for prolonged network lifetime. Ad Hoc Networks, 9(5), 835–851.

    Article  Google Scholar 

  2. Liu, D., Zhang, K., & Ding, J. (2013). Energy-efficient transmission scheme for mobile data gathering in wireless sensor networks. China Communications, 10(3), 114–123.

    Article  MathSciNet  Google Scholar 

  3. Han, Z., Wu, J., Zhang, J., Liu, L., & Tian, K. (2014). A general self-organized tree-based energy-balance routing protocol for wireless sensor network. IEEE Transactions on Nuclear Science, 61(2), 732–740.

    Article  Google Scholar 

  4. Ren, F., Zhang, J., He, T., Lin, C., & Das, S. K. (2011). EBRP: Energy-balanced routing protocol for data gathering in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22(12), 2108–2125.

    Article  Google Scholar 

  5. Zhang, D., Li, G., Zheng, K., & Ming, X. (2014). An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Transactions on Industrial Informatics, 10(1), 766–773.

    Article  Google Scholar 

  6. Kang, J., Zhang, Y., & Nath, B. (2007). TARA: Topology-aware resource adaptation to alleviate congestion in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 18(7), 919–931.

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Bouabdallah, F., Bouabdallah, N., & Boutaba, R. (2009). On balancing energy consumption in wireless sensor networks. IEEE Transactions on Vehicular Technology, 58(6), 2909–2924.

    Article  Google Scholar 

  9. 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 

  10. 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 

  11. Paek, J., & Govindan, R. (2007). RCRT: Rate-controlled reliable transport for wireless sensor networks. In Proceedings of the ACM international conference on embedded networked sensor systems (SenSys ’07).

  12. Rangwala, S., Gummadi, R., Govindan, R., & Psounis, K. (2006). Interference-aware fair rate control in wireless sensor networks. In Proceedings of the ACM SIGCOMM, pp. 63–74.

  13. Villas, L., Boukerche, A., & Filho, H. R. (2013). DRINA: A lightweight and reliable routing approach for in-network aggregation in wireless sensor networks. IEEE Transactions on Computers, 62(4), 676–689.

    Article  Google Scholar 

  14. Tufail, A., Qamar, A., & Khan, A. M. (2013). WEAMR—A weighted energy aware multipath reliable routing mechanism for hotline-based WSNs. Sensors, 13(5), 6295–6318.

    Article  Google Scholar 

  15. El-Semary, A. M., & Azim, M. M. (2011). Path energy weight: A global energy-aware routing protocol for wireless sensor networks. In Proceedings of the WD, Venice, pp. 1–6.

  16. AlShawi, I. S., Yan, L., & Pan, W. (2012). Lifetime enhancement in wireless sensor networks using fuzzy approach and A-star algorithm. IEEE Sensors Journal, 12(10), 3010–3018.

    Article  Google Scholar 

  17. Kumar, R., Crepaldi, R., Rowaihy, H., & Harris, A. F. (2008). Mitigating performance degradation in congested sensor networks. IEEE Transactions on Mobile Computing, 7(6), 682–697.

    Article  Google Scholar 

  18. Zhang, Z., & Cui, G. (2008). An effective congestion avoidance altering routing protocol in sensor networks. In Proceedings of the ICCSSE, pp. 980–983.

  19. 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 

  20. Wang, C., Li, B., Sohraby, K., Daneshmand, M., & Hu, Y. (2007). Upstream congestion control in wireless sensor networks through cross-layer optimization. IEEE Journal on Selected Areas in Communications, 25(4), 786–795.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported in part by the National High Technology Research and Development of China (863 Program) under Grant 2014AA01A701, and in part by the Beijing Natural Science Foundation under Grant 4142049.

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 & Sen Feng

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. Sen Feng
    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. & Feng, S. Traffic-Aware and Energy-Efficient Routing Algorithm for Wireless Sensor Networks. Wireless Pers Commun 85, 2669–2686 (2015). https://doi.org/10.1007/s11277-015-2927-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2927-8

Keywords

Search

Navigation