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Wireless Networks

, Volume 20, Issue 6, pp 1239–1250 | Cite as

Dynamic traffic-aware routing algorithm for multi-sink wireless sensor networks

  • Do Duy Tan
  • Dong-Seong KimEmail author
Article

Abstract

In this paper, a distributed traffic-balancing routing algorithm is proposed for multi-sink wireless sensor networks that effectively distributes traffic from sources to sinks. Each node has a gradient field that is used to decide on a neighbor node to reach a sink. The node’s gradient index contains (1) the distance cost from a source to a respective sink, and (2) traffic information from neighboring nodes. The proposed algorithm considers the traffic being faced by surrounding neighbors before forwarding packets to any sink using gradient search for routing and providing a balance between optimal paths and possible congestion on routes toward those sinks. The key objective of this work is to achieve traffic-balancing by detecting congested areas along the route and distributing packets along paths that have idle and underloaded nodes. Extensive simulations conducted to evaluate the performance of the proposed scheme indicate that it effectively reduces the overall packet delay, energy consumption and improves the packet delivery ratio under heavy traffic.

Keywords

Multiple sinks Traffic-aware Wireless sensor networks Gradient End-to-end delay Packet delivery ratio Energy consumption 

Notes

Acknowledgments

The authors would like to convey thanks to Faculty of Electrical and Electronics Engineering, University of Technical Education Ho Chi Minh City, Vietnam and Networked Systems Lab., School of Electronic Engineering, Kumoh National Institute of Technology, South Korea for providing laboratory facilities. This research was financially supported by National Research Foundation of Korea (NRF) through the Human Resource Training Project for Regional Innovation 2013 and Basic Science Research Program (NO. 2011-0025409).

References

  1. 1.
    Akkaya, K., & Younis, M. (2005) A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3, 325–349.CrossRefGoogle Scholar
  2. 2.
    Al-Karaki, J., & Kamal, A. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications, 11(6), 6–28.CrossRefGoogle Scholar
  3. 3.
    Basu, A., Lin, A., & Ramanathan, S. (2003) Routing using potentials: A dynamic traffic-aware routing algorithm. In Proceedings of the 2003 conference on applications, technologies, architectures, and protocols for computer communications, SIGCOMM, pp. 37–48.Google Scholar
  4. 4.
    Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1 (1), 269–271.CrossRefzbMATHMathSciNetGoogle Scholar
  5. 5.
    Dinh, N. Q., Hoa, T. D., & Kim, D. S. (2011). Distributed traffic aware routing with multiple sinks in wireless sensor networks. In 9th IEEE international conference on industrial informatics (INDIN), pp. 404 –409.Google Scholar
  6. 6.
    Gao, D., Zheng, T., Zhang, S., & Yang, O. W. W. (2010). Improved gradient-based micro sensor routing protocol with node sleep scheduling in wireless sensor networks. In IEEE 72nd vehicular technology conference fall (VTC 2010-Fall), pp. 1–5.Google Scholar
  7. 7.
    Heinzelman, W., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii international conference on system sciences, Vol. 2, p. 10.Google Scholar
  8. 8.
    Heo, J., Hong, J., & Cho, Y. (2009). EARQ: Energy aware routing for real-time and reliable communication in wireless industrial sensor networks. IEEE Transactions on Industrial Informatics, 5 (1), 3–11.CrossRefGoogle Scholar
  9. 9.
    Huang, P., Chen, H., Xing, G., & Tan, Y. (2009). SGF: A state-free gradient-based forwarding protocol for wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5, 14:1–14:25.CrossRefGoogle Scholar
  10. 10.
    IETF ROLL WG. (2010). RPL: Routing protocol for low power and lossy networks. In IETF internet-draft. IETF ROLL WG, March 8.Google Scholar
  11. 11.
    Intanagonwiwat, C., Govindan, R., Estrin D., Heidemann, J., & Silva, F., (2003). Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking, 11(1), 2–16.CrossRefGoogle Scholar
  12. 12.
    Kanavalli, A., Jayashree, M., Shenoy, P., Venugopal, K., & Patnaik, L. (2008). Hop by hop congestion control system for adhoc networks. In IEEE region 10 conference TENCON, pp. 1–4.Google Scholar
  13. 13.
    Li, Y., Chen, C. S., Song, Y. Q., Wang, Z., & Sun, Y. (2009). Enhancing real-time delivery in wireless sensor networks with two-hop information. IEEE Transactions on Industrial Informatics, 5 (2), 113–122.CrossRefGoogle Scholar
  14. 14.
    Mei, A., Piroso, N., & Vavala, B. (2012). Fine grained load balancing in multi-hop wireless networks. Journal of Parallel and Distributed Computing, 72 (4), 475–488.CrossRefGoogle Scholar
  15. 15.
    Mottola, L., & Picco, G. (2011). Muster: Adaptive energy-aware multisink routing in wireless sensor networks. IEEE Transactions on Mobile Computing, 10(12), 1694–1709.CrossRefGoogle Scholar
  16. 16.
    Park, C., & Jung, I. (2010). Traffic-aware routing protocol for wireless sensor networks. In International conference on information science and applications (ICISA), pp. 1 –8.Google Scholar
  17. 17.
    Pussente, R. M., & Barbosa, V. C. (2009). An algorithm for clock synchronization with the gradient property in sensor networks. Journal of Parallel and Distributed Computing, 69 (3), 261–265.CrossRefGoogle Scholar
  18. 18.
    Quang, P. T. A., & Kim, D. S. (2012). Enhancing real-time delivery of gradient routing for industrial wireless sensor networks. IEEE Transactions on Industrial Informatics, 8(1), 61–68.CrossRefGoogle Scholar
  19. 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.CrossRefGoogle Scholar
  20. 20.
    Schurgers, C., & Srivastava, M. (2001). Energy efficient routing in wireless sensor networks. In IEEE military communications conference, Vol. 1, pp. 357–361.Google Scholar
  21. 21.
    Shah-Mansouri, V., Mohsenian-Rad, A. H., & Wong, V. (2009). Lexicographically optimal routing for wireless sensor networks with multiple sinks. IEEE Transactions on Vehicular Technology, 58(3), 1490–1500.CrossRefGoogle Scholar
  22. 22.
    Slama, I., Jouaber, B., & Zeghlache, D. (2008). Energy efficient scheme for large scale wireless sensor networks with multiple sinks. In Wireless communications and networking conference, pp. 2367–2372.Google Scholar
  23. 23.
    Suhonen, J., Kuorilehto, M., Hannikainen, M., & Hamalainen, T. (2006). Cost-aware dynamic routing protocol for wireless sensor networks-design and prototype experiments. In IEEE 17th international symposium on personal, indoor and mobile radio communications, pp. 1–5.Google Scholar
  24. 24.
    Torfs, T., Sterken, T., Brebels, S., Santana, J., van den Hoven , R., Spiering, V. et al. (2013). Low power wireless sensor network for building monitoring. IEEE Sensors Journal, 13(3), 909–915.CrossRefGoogle Scholar
  25. 25.
    yih Wan C., & Eisenman S. B. (2003). CODA congestion detection and avoidance in sensor networks (pp. 266–279). New york: ACM Press.Google Scholar
  26. 26.
    Watteyne, T., Pister, K., Barthel, D., Dohler, M., & Auge-Blum, I. (2009). Implementation of gradient routing in wireless sensor networks. In Proceedings of the 28th IEEE conference on global telecommunications, GLOBECOM, pp. 5331–5336.Google Scholar
  27. 27.
    Yang, J., Zhang, C., Li, X., Huang, Y., Fu, S., & Acevedo, M. (2010). Integration of wireless sensor networks in environmental monitoring cyber infrastructure. Wireless Networks, 16 (4), 1091–1108.CrossRefGoogle Scholar
  28. 28.
    Yoo, H., Shim, M., Kim, D., & Kim, K. H. (2010). GLOBAL: A gradient-based routing protocol for load-balancing in large-scale wireless sensor networks with multiple sinks. In IEEE symposium on computers and communications (ISCC), pp. 556–562.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Faculty of Electrical and Electronics EngineeringUniversity of Technical Education Ho Chi Minh CityHo Chi Minh CityVietnam
  2. 2.School of Electronic EngineeringKumoh National Institute of TechnologyGumi-siSouth Korea

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