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Wireless Networks

, Volume 24, Issue 5, pp 1755–1774 | Cite as

Traffic-aware stateless multipath routing for fault-tolerance in IEEE 802.15.4 wireless mesh networks

  • Kiwoong Kwon
  • Seong Hoon Kim
  • Minkeun Ha
  • Daeyoung Kim
Article

Abstract

Single-path routing is widely used in wireless networks due to low resource consumption. However, it is vulnerable to link failure because such a failure may adversely affect an entire path. To overcome this, multipath routing has been proposed providing fault-tolerance. In this paper, we propose a novel multipath routing protocol called traffic-aware stateless multipath routing (TSMR) based on an overlaid tree topology comprising two topologies, namely, bounded degree tree (BDT) and root-oriented directional tree (RODT). BDT is strong on reducing routing overhead, and RODT is resilient against lossy links. By synergistically overlaying them, TSMR dynamically selects the local optimal path according to the given traffic flow and the failure on the primary path. In particular, TSMR enables stateless and low overhead routing despite multipath routing by keeping only one-hop neighbors to maintain multiple paths. To evaluate TSMR, we conducted simulations with a shadowing model reflecting lossy links, and compared with single and multipath routing protocols, such as ZTR, STR, AODV, and RPL. The simulation results show that the overall performance of TSMR surpasses that of others for packet delivery ratio, end-to-end delay, control overhead, memory consumption, and power consumption regardless of network size, number of sessions, and traffic flow.

Keywords

Multipath routing Fault-tolerance Tree routing Resource constraints IEEE 802.15.4 Wireless mesh networks 

Notes

Acknowledgements

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R01261610020001002, Development of agro-livestock cloud and application service for balanced production, transparent distribution and safe consumption based on GS1) and National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Supplementary material

11276_2016_1427_MOESM1_ESM.pdf (770 kb)
Supplementary material 1 (pdf 769 KB)

References

  1. 1.
    Kwon, K., Ha, M., Kim, S., & Kim, D. (2013). TAMR: Traffic aware multipath routing for fault tolerance in 6LoWPAN. In IEEE global communications conference (GLOBECOM) (pp. 109–114).Google Scholar
  2. 2.
    Akyildiz, I. F., & Wang, X. (2005). A survey on wireless mesh networks. IEEE Communications Magazine, 43(9), S23–S30.CrossRefGoogle Scholar
  3. 3.
    Lee, M., Zhang, R., Zhu, C., Park, T., Shin, C., Jeon, Y., et al. (2013). Meshing wireless personal area networks: Introducing IEEE 802.15.5. IEEE Communications Magazine, 48(1), 54–56.CrossRefGoogle Scholar
  4. 4.
    Radi, M., Dezfouli, B., Bakar, K. A., & Lee, M. (2012). Multipath routing in wireless sensor networks: Survey and research challenges. Sensors-Basel, 12(1), 650–685.CrossRefGoogle Scholar
  5. 5.
    sha, K., Gehlot, J., & Greve, R. (2013). Multipath routing techniques in wireless sensor networks: A survey. Wireless Personal Communications, 70(2), 807–829.CrossRefGoogle Scholar
  6. 6.
    Winter, T., Thubert, P., Brandt, A., Clausen, T., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur, J. P., & Alexander, R. (2012). RPL: IPv6 routing protocol for low power and lossy networks. In IETF Roll WG. Accessed Aug 1, 2016, from https://tools.ietf.org/html/rfc6550.
  7. 7.
    Ko, Y., & Vaidya, H. (2000). Location-aided routing (LAR) in mobile ad hoc networks. Wireless Networks, 6(4), 307–321.CrossRefzbMATHGoogle Scholar
  8. 8.
    Kim, T., Kim, S., Yang, J., Yoo, S., & Kim, D. (2014). Neighbor table based shortcut tree routing in ZigBee wireless networks. IEEE Transactions on Parallel Distributed Systems, 25(3), 706–716.CrossRefGoogle Scholar
  9. 9.
    Sturek, D. (2006). ZigBee alliance. Accessed Aug 1, 2016, from https://zigbee.org.
  10. 10.
    Chakeres, I. D., & Klein-Berndt, L. (2002). AODVjr, AODV simplified. ACM SIGMOBILE Mobile Computing and Communications Review, 6(3), 100–101.CrossRefGoogle Scholar
  11. 11.
    Mulligan, G., & 6LoWPAN WG. (2007). The 6LoWPAN architecture. In The 4th workshop on embedded networked sensors (pp. 78–82).Google Scholar
  12. 12.
    Hui, J., & Thubert, P. (2011). Compression format for IPv6 datagrams over IEEE 802.15.4-based networks. In IETF 6Lo WG. Accessed Aug 1, 2016, from https://tools.ietf.org/html/rfc6282.
  13. 13.
    Kim, K., Yoo, S., Park, Daniel, S., & Lee, J. (2007). Hierarchical routing over 6LoWPAN (HiLow). In IETF Internet-Draft. Accessed Aug 1, 2016, from https://tools.ietf.org/html/draft-daniel-6lowpan-hilow-hierarchical-routing-01.
  14. 14.
    Gnawali, O., Fonseca, R., Jamieson, K., Moss, D., & Levis, P. (2009). Collection tree protocol. In The 7th ACM conference on embedded networked sensor systems (SenSys) (pp. 1–14).Google Scholar
  15. 15.
    Couto, D., Aguayo, D., Bicket, J., & Morris, R. (2005). A high-throughput path metric for multi-hop wireless routing. Wireless Networks, 11(4), 419–434.CrossRefGoogle Scholar
  16. 16.
    Radi, M., Dezfouli, B., Bakar, K. A., Razak, S. A., & Lee, M. (2015). LINKORD: Link ordering-based data gathering protocol for wireless sensor networks. Computing, 97(3), 205236.CrossRefGoogle Scholar
  17. 17.
    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.CrossRefGoogle Scholar
  18. 18.
    Kim, K., Park, D., Montenegro, G., Yoo, S., & Kushalngar, N. (2007). 6LoWPAN ad hoc on-demand distance vector routing (LOAD). In IETF Internet-Draft. Accessed Aug 1, 2016, from https://tools.ietf.org/html/draft-daniel-6lowpan-load-adhoc-routing-03.
  19. 19.
    Kwon, K., Ha, M., Kim, T., Kim, S., & Kim, D. (2012). The stateless point to point routing protocol based on shortcut tree routing algorithm for IP-WSN. In IEEE 3rd international conference on the Internet of Things (IoT) (pp. 167–174).Google Scholar
  20. 20.
    Hong, S., Kim, D., Ha, M., Bae, S., Park, S., Jung, W., et al. (2010). SNAIL: An IP-based wireless sensor network approach to the internet of things. IEEE Wireless Communications, 17(6), 34–42.CrossRefGoogle Scholar
  21. 21.
    Ha, J. Y., Park, H. S., Choi, S., & Kwon, W. H. (2007). Ehrp: Enhanced hierarchical routing protocol for ZigBee mesh networks. IEEE Communications Letter, 11(12), 1028–1030.CrossRefGoogle Scholar
  22. 22.
    Liu, Y., & Qian, K. (2016). A novel tree-based routing protocol in ZigBee wireless networks. In 8th IEEE international conference on communication software and networks (ICCSN) (pp. 469–473).Google Scholar
  23. 23.
    Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: A scalable and robust communication paradigm for sensor networks. In The 6th annual international conference on mobile computing and networking (MobiCom) (pp. 56–67).Google Scholar
  24. 24.
    Ganesan, D., Govindan, R., Shenker, S., & Estrin, D. (2001). Highly-resilient, energy-efficient multipath routing in wireless sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review, 5(4), 11–25.CrossRefGoogle Scholar
  25. 25.
    Pavkoivic, B., Theoleyre, F., & Duda, A. (2011). Multipath opportunistic RPL routing over IEEE 802.15.4. In The 14th ACM international conference on modeling, analysis and simulation of wireless and mobile systems (pp. 179–186).Google Scholar
  26. 26.
    Biswas, S., & Morris, R. (2005). ExOR: Opportunistic multi-hop routing for wireless networks. In The annual conference of the special interest group on data communication (SIGCOMM) (pp. 133–144).Google Scholar
  27. 27.
    Moghadam, M. N., & Taheri, H. (2015). Multi-class multipath routing protocol for low power wireless networks with heuristic optimal load distribution. Wireless Personal Communications, 82(2), 861–881.CrossRefGoogle Scholar
  28. 28.
    Moghadam, M. N., Taheri, H., & Karrari, M. (2014). Minimum cost load balanced multipath routing protocol for low power and lossy networks. Wireless Networks, 20(8), 2469–2479.CrossRefGoogle Scholar
  29. 29.
    Raid, M., Dezfouli, B., Bakar, K. A., Razak, S. A., & Hwee-Pink, T. (2014). IM2PR: Interference-minimized multipath routing protocol for wireless sensor networks. Wireless Networks, 20(7), 1807–1823.CrossRefGoogle Scholar
  30. 30.
    Goyal, M., Baccelli, E., Philipp, M., Brandt, A., & Martocci, J. (2013). Reactive discovery of point-to-point routes in low-power and lossy networks. IETF Roll WG. Accessed Aug 1, 2016, from https://tools.ietf.org/html/rfc6997.
  31. 31.
    Kim, K., Park, D., Montenegro, G., Yoo, S., & Kushalngar, N. (2010). Hydro: A hybrid routing protocol for low-power and lossy networks. In The 1st IEEE conference on smart grid communications (SmardGridComm) (pp. 268–273).Google Scholar
  32. 32.
    Baronti, P., Pillai, P., Chook, V. W. C., Chessa, S., Gotta, A., & Hu, Y. F. (2007). Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Computer Communications, 30(7), 1655–1695.CrossRefGoogle Scholar
  33. 33.
    Kim, E., Kaspar, D., & Vasseur, J. P. (2012). Design and application spaces for IPv6 over low-power wireless personal area networks (6LoWPANs). In IETF 6Lo WG. Accessed Aug 1, 2016, from https://tools.ietf.org/html/rfc6568
  34. 34.
    Willig, A. (2008). Recent and emerging topics in wireless industrial communications: A selection. IEEE Transactions on Industrial Information, 4(2), 102–124.CrossRefGoogle Scholar
  35. 35.
    Gomez, C., & Paradells, J. (2010). Wireless home automation networks: A survey of architectures and technologies. IEEE Communications Magazine, 48(6), 92–101.CrossRefGoogle Scholar
  36. 36.
    Zhao, J., & Govindan, R. (2003). Understanding packet delivery performance in dense wireless sensor networks. In The 1st international conference on embedded networked sensor systems (Sensys), Los Angeles (pp. 1–13).Google Scholar
  37. 37.
    Kotz, D., Newport, C., & Elliott, C. (2003). The mistaken axioms of wireless-network research. Dartmouth Computer Science Technical Report TR2003-467. Accessed Aug 1, 2016, from http://www.cs.dartmouth.edu/reports/TR2003-467.
  38. 38.
    Dezfouli, B., Radi, M., Razaka, S. A., Hwee-Pink, T., & Bakar, K. A. (2015). Modeling low-power wireless communications. Journal of Network and Computer Applications, 51, 102–126.CrossRefGoogle Scholar
  39. 39.
    Kim, S. H., Chong, P. K., & Kim, D. (2014). A location-free semi-directional-flooding technique for on-demand routing in low-rate wireless mesh networks. IEEE Transactions on Parallel Distributed Systems, 25(12), 3066–3075.CrossRefGoogle Scholar
  40. 40.
    Hui, J. W., & Culler, D. E. (2008). IP is dead, long live IP for wireless sensor networks. In The proceedings of the 6th ACM conference on embedded network sensor systems (SenSys 08) (pp. 15–28).Google Scholar
  41. 41.
    Latr, B., Mil, P. D., Moerman, I., Dhoed, B., Demeester, P., & Dierdonck, N. V. (2006). Throughput and delay analysis of unslotted IEEE 802.15. 4. Journal of Networks, 1(1), 20–28.Google Scholar
  42. 42.
    Pan, M., & Tseng, Y. (2009). A lightweight network repair scheme for data collection applications in ZigBee WSNs. IEEE Communications Letter, 13(9), 649–651.CrossRefGoogle Scholar
  43. 43.
    Issariyakul, T., & Hossain, E. (2011). Introduction to network simulator NS2 (2nd ed.). New York: Springer.Google Scholar
  44. 44.
    Rappaport, T. S. (2002). Wireless communications: Principles and practice (2nd ed.). Englewood Cliffs, NJ: Prentice Hall.zbMATHGoogle Scholar
  45. 45.
    Gungor, V., Lu, B., & Hancke, G. (2010). Opportunities and challenges of wireless sensor networks in smart grid. IEEE Transactions on Industrial Electronics, 57(10), 3557–3564.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of School of ComputingKorea Advanced Institute of Science and Technology (KAIST)DaejeonKorea
  2. 2.Software GroupYBrainSeongnamKorea
  3. 3.School of Technology and HealthKTH Royal Institute of TechnologyStockholmSweden

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