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A hybrid beaconless geographic routing for different packets in WSN

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Abstract

The localized operation and stateless features of geographic routing make it become an attractive routing scheme for wireless sensor network (WSN). In this paper, we proposed a novel routing protocol, hybrid beaconless geographic routing (HBGR), which provides different mechanisms for different packets. Based on the requirement of application on latency, we divide the packets of WSN into delay sensitive packets and normal packets. HBGR uses two kinds of Request-To-Send/Clear-To-Send handshaking mechanisms for delay sensitive packets and normal packets, and assigns them different priority to obtain the channel. The simplified analysis is given, which proves that delay sensitive packets have lower latency and higher priority to obtain the channel than normal packets. Moreover, forwarding area division scheme is proposed to optimize the forwarder selection. Simulation results show that HBGR achieves higher packet delivery ratio, lower End-to-End latency and lower energy consumption than existing protocols under different packet generation rates in stationary and mobility scenario. Besides, compared with normal packets, delay sensitive packets have at least 10 % (9 %) improvement in terms of End-to-End latency. The improvement increases with the increasing of packet generation rate, and achieves 58 % (73 %) when the packet generation rate is 24 packets per second in stationary (mobility) scenario.

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References

  1. Chen, D., & Varshney, P. K. (2007). A survey of void handling techniques for geographic routing in wireless networks. IEEE Communication on Surveys & Tutorials, 9(1), 50–67.

    Article  Google Scholar 

  2. Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 15(2), 551–591.

    Article  Google Scholar 

  3. Sheng, Z., Yang, S., Yu, Y., et al. (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 

  4. 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 

  5. Vasilakos, A., et al. (2012). Delay tolerant networks: Protocols and applications. Boca Raton: CRC Press.

    Google Scholar 

  6. Chen, M., Leung, V. C. M., Mao, S., et al. (2009). Hybrid geographic routing for flexible energy-delay trade-offs. IEEE Transactions on Vehicular Technology, 58(9), 4976–4988.

    Article  Google Scholar 

  7. Park, J., Kim, Y. N., & Byun, J. Y. (2013). A forwarder selection method for greedy mode operation of a geographic routing protocol in a WSN. In Fifth international conference on ubiquitous and future networks (ICUFN), Da Nang (pp. 270–275).

  8. Karp, B., & Kung, H. T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In 6th annual ACM/IEEE international conference on mobile computing and networking (MobiCom 2000), Boston.

  9. Leong, B., Liskov, B., & Morris, R. (2006). Geographic routing without planarization. In 3rd conference on networked systems design and implementation, San Jose (pp. 25–39).

  10. Zou, L., Lu, M., & Xiong, Z. (2007). PAGER-M: A novel location-based routing protocol for mobile sensor networks. In 2007 ACM SIGMOD international conference on management of data, Beijing (pp. 1182–1185).

  11. Yu, Y., Govindan, R., & Estrin, D. (2001). Geographical and energy aware routing: A recursive data dissemination protocol for wireless sensor networks. UCLA Computer Science Department Technical Report.

  12. Zeng, Y., Xiang, K., Li, D., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  13. Blum, B. M., He, T., Son, S., et al. (2003). IGF: A state-free robust communication protocol for wireless sensor networks. Technical Report CS-2003-11: Department of Computer Science, University of Virginia.

  14. Chen, D., & Varshney, P. K. (2007). On-demand geographic forwarding for data delivery in wireless sensor networks. Computer Communications, 30(14–15), 2954–2967.

    Article  Google Scholar 

  15. Casari, P., Nati, M., Petrioli, C., et al. (2006). ALBA: An adaptive loadCbalanced algorithm for geographic forwarding in wireless sensor networks. In IEEE military communications conference (MILCOM), Washington, DC.

  16. Casari, P., Nati, M., Petrioli, C., et al. (2007). Efficient non-planar routing around dead ends in sparse topologies using random forwarding. In IEEE international conference on communications, Glasgow (pp. 3122–3129).

  17. Lima, C., & Abreu, G. T. F. D. (2008). Game-theoretical relay selection strategy for geographic routing in multi-hop WSNs. In 5th workshop on positioning, navigation and communication 2008 (WPNC’08), Germany (pp. 277–283).

  18. Zorzi, M., & Rao, R. R. (2003). Geographic random forwarding (GeRaF) for ad hoc and sensor networks: Energy and latency performance. IEEE Transactions on Mobile Computing, 2(4), 349–365.

    Article  Google Scholar 

  19. Zorzi, M., & Rao, R. R. (2003). Geographic random forwarding (GeRaF) for ad hoc and sensor networks: Multihop performance. IEEE Transactions on Mobile Computing, 2(4), 337–348.

    Article  Google Scholar 

  20. Zhang, H., & Shen, H. (2010). Energy-efficient beaconless geographic routing in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 21(6), 881–896.

    Article  Google Scholar 

  21. Xiang, L., Luo, J., & Vasilakos, A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In 2011 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON), Salt Lake City, UT (pp. 46–54).

  22. Wei, G., Ling, Y., Guo, B., et al. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter. Computer Communications, 34(6), 793–802.

    Article  Google Scholar 

  23. Liu, X., Zhu, Y., Kong, L., et al. (2014). CDC compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems , 26(8), 2188–2197.

    Article  Google Scholar 

  24. Meng, T., Wu, F., Yang, Z., et al. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE Transactions on Computers. doi:10.1109/TC.2015.2417543.

  25. Li, P., Guo, S., Yu, S., et al. (2012). CodePipe: An opportunistic feeding and routing protocol for reliable multicast with pipelined network coding. In 2012 proceedings IEEE INFOCOM, Orlando, FL (pp. 100–108).

  26. Li, P., Guo, S., Yu, S., et al. (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. Cheng, H., Xiong, N., Vasilakos, A. V., et al. (2012). Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks. Ad Hoc Networks, 10(5), 760–773.

    Article  Google Scholar 

  28. Song, Y., Liu, L., Ma, H., et al. (2014). Physarum optimization is a biology-inspired algorithm which could be used for improving the quality of coverage in WSN. IEEE Transactions on Network and Service Management, 11(3), 417–430.

    Article  Google Scholar 

  29. Liu, L., Song, Y., Zhang, H., et al. (2015). Physarum optimization: A biology-inspired algorithm for the Steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 819–832.

    MathSciNet  Google Scholar 

  30. Yao, Y., Cao, Q., & Vasilakos, A. V. (2013). EDAL: an energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In 2013 IEEE 10th international conference on mobile ad-hoc and sensor systems (MASS), Hangzhou (pp. 182–190).

  31. 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 

  32. Liu, Y., Xiong, N., Zhao, Y., et al. (2009). Multi-layer clustering routing algorithm for wireless vehicular sensor networks. IET Communications, 4(7), 810–816.

    Article  Google Scholar 

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

    Article  Google Scholar 

  34. Chilamkurti, N., Zeadally, S., Vasilakos, A., et al. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors2009, 1–9.

    Article  Google Scholar 

  35. Jamieson, K., Balakrishnan, H., & Tay, Y. C. (2006). Sift: A MAC protocol for event-driven wireless sensor networks. In 3rd European workshop on wireless sensor networks (EWSN’06), Zurich, Switzerland (pp. 260–275).

  36. Perkins, C. E., & Royer, E. M. (1999). Ad-hoc on-demand distance vector routing. In 2nd IEEE workshop on mobile computing systems and applications.

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Correspondence to Chao Hong.

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Hong, C., Xiong, Z. & Zhang, Y. A hybrid beaconless geographic routing for different packets in WSN. Wireless Netw 22, 1107–1120 (2016). https://doi.org/10.1007/s11276-015-1020-2

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