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A MAC transmission strategy in sparse Vehicular Delay-Tolerant Sensor Networks

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Abstract

In wireless sensor networks that lack telecommunication infrastructure, vehicular sensors may experience the following severe connectivity issues: sparse and intermittent connectivity, long and variable delays, high latency, high error rates, highly asymmetric data rates, and lack of end-to-end connectivity. The MAC layer can make use of this connectivity problem and play an important role in solving data throughput efficiency, energy conservation and different service issues in sparse Vehicular Delay-Tolerant Sensor Networks (VDTSN). In this paper we propose an efficient transmission strategy in the MAC layer which coordinates the working procedure of vehicular sinks and ordinary sensors. We also designed three transmission algorithms for different quality requirements of data, with energy conservation considerations in one contact interval. Transmission power consumption and data throughput are the main measurements used to evaluate transmission efficiency performance. We compare and analyse our scheme with two other important MAC protocols in wireless sensor networks and vehicular ad-hoc networks in throughput, delay, energy consumption etc. The simulation results show that the strategy performs the transmission of different types of data more effectively in an energy-saving and data-throughput-balanced way than other MAC approaches in sparse VDTSN.

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References

  1. Ehsan, S., Bradford, K., Brugger, M., Hamdaoui, B., Kovchegov, Y., Johnson, D., et al. (2012). Design and analysis of delay-tolerant sensor networks for monitoring and tracking free-roaming animals. IEEE Transactions on Wireless Communications, 11(3), 1220–1227.

    Article  Google Scholar 

  2. Piran, M. J., Murthy, G. R., & Babu, G. P. (2011). Vehicular ad hoc and sensor networks; principles and challenges. CoRR. arXiv:1108.2776.

  3. Pereira, P. R., Casaca, A., Rodrigues, J. J. P. C., Soares, V. N. G. J., Triay, J., & Cervello-Pastor, C. (2012). From delay-tolerant networks to vehicular delay-tolerant networks. Fourth IEEE Communications Surveys Tutorials, 14(4), 1166–1182.

    Article  Google Scholar 

  4. De Zoysa, K., Keppitiyagama, C., Seneviratne, G. P., & Shihan, W. W. A. T. (2007). A public transport system based sensor network for road surface condition monitoring. In Proceedings of the 2007 workshop on networked systems for developing regions (ser. NSDR ’07) (pp. 9:1–9:6). New York, NY, USA: ACM. Doi:10.1145/1326571.1326585

  5. Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, et al. (2006). Cartel: A distributed mobile sensor computing system. In Proceedings of the 4th international conference on embedded networked sensor systems (ser. SenSys ’06) (pp. 125–138). New York, NY, USA: ACM. Doi:10.1145/1182807.1182821

  6. Murillo, M., & Aukin, M. (2011). Application of wireless sensor nodes to a delay-tolerant health and environmental data communication system in remote communities. IEEE Global Humanitarian Technology Conference (GHTC), 2011, 2011, 383–392.

    Article  Google Scholar 

  7. Guo, S., Falaki, M. H., Oliver, E. A., Ur Rahman, S., Seth, A., Zaharia, M. A., & Keshav, S. (2007). Very low-cost internet access using kiosknet. SIGCOMM Computer Communication Review, 37(5), 95–100. Doi:10.1145/1290168.1290181

  8. Uddin, M., Nicol, D., Abdelzaher, T., & Kravets, R. (2009). A post-disaster mobility model for delay tolerant networking. In Proceedings of the 2009 winter simulation conference (WSC), pp. 2785–2796.

  9. Dang, H., & Wu, H. (2009). Mobility models for delay-tolerant mobile networks. In Third international conference on sensor technologies and applications, 2009 (SENSORCOMM ’09), June 2009, pp. 55–60.

  10. Bachir, A., Dohler, M., Watteyne, T., & Leung, K. (2010). Mac essentials for wireless sensor networks. IEEE Communications Surveys Tutorials, 12(2), 222–248.

    Article  Google Scholar 

  11. Idoudi, H., Hmili, N., & Saidane, L. (2011). Energy efficient cross-layer architecture for wireless sensor networks. In 11th mediterranean microwave symposium (MMS), 2011, September 2011, pp. 126–129.

  12. Doudou, M., Djenouri, D., & Badache, N. (2013). Survey on latency issues of asynchronous mac protocols in delay-sensitive wireless sensor networks. Second IEEE Communications Surveys Tutorials, 15(2), 528–550.

    Article  Google Scholar 

  13. Suriyachai, P., Roedig, U., & Scott, A. (2012). A survey of mac protocols for mission-critical applications in wireless sensor networks. Second IEEE Communications Surveys Tutorials, 14(2), 240–264.

    Article  Google Scholar 

  14. Zhou, X., & Boukerche, A. (2014). An efficient transmission strategy in 802.11 mac in wireless delay-tolerant sensor network. In IEEE international conference on communications (ICC), 2014, June 2014, pp. 5497–5502.

  15. Boukerche, A. (2008). Algorithms and protocols for wireless, mobile ad hoc networks (Vol. 77). New York: Wiley.

    Book  Google Scholar 

  16. Boukerche, A. (2008). Algorithms and protocols for wireless sensor networks (Vol. 62). New York: Wiley.

    Book  Google Scholar 

  17. Booysen, M., Zeadally, S., & van Rooyen, G.-J. (2011). Survey of media access control protocols for vehicular ad hoc networks. IET Communications, 5(11), 1619–1631.

    Article  Google Scholar 

  18. Natkaniec, M., Kosek-Szott, K., Szott, S., & Bianchi, G. (2013). A survey of medium access mechanisms for providing qos in ad-hoc networks. IEEE Communications Surveys Tutorials, 15(2), 592–620.

    Article  Google Scholar 

  19. K. Langendoen. (2008). Medium access control in wireless sensor networks. In Medium access control in wireless networks, Vol. 2, pp. 535–560.

  20. Kredo, K., II & Mohapatra, P. (2007). Medium access control in wireless sensor networks. Computer Networks, 51(4), 961–994. Doi:10.1016/j.comnet.2006.06.012

  21. Demirkol, I., Ersoy, C., & Alagoz, F. (2006). Mac protocols for wireless sensor networks: A survey. IEEE Communications Magazine, 44(4), 115–121.

    Article  Google Scholar 

  22. Ringwald, M., & Romer, K. (2005). Bitmac: A deterministic, collision-free, and robust mac protocol for sensor networks. In Proceeedings of the second European workshop on wireless sensor networks, 2005, January 2005, pp. 57–69.

  23. Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient mac protocol for wireless sensor networks. In INFOCOM 2002. Twenty-first annual joint conference of the IEEE computer and communications societies. Proceedings (Vol. 3, pp. 1567–1576). IEEE.

  24. van Dam, T., & Langendoen, K. (2003). An adaptive energy-efficient mac protocol for wireless sensor networks. In Proceedings of the 1st international conference on embedded networked sensor systems (ser. SenSys ’03). (pp. 171–180). New York, NY, USA: ACM. Doi:10.1145/958491.958512

  25. IEEE standard for information technology—local and metropolitan area networks- specific requirements- part 11: wireless lan medium access control (mac) and physical layer (phy) specifications amendment 8: Ieee 802.11 wireless network management. IEEE Std 802.11v-2011 (Amendment to IEEE Std 802.11-2007 as amended by IEEE Std 802.11k-2008, IEEE Std 802.11r-2008, IEEE Std 802.11y-2008, IEEE Std 802.11w-2009, IEEE Std 802.11n-2009, IEEE Std 802.11p-2010, and IEEE Std 802.11z-2010). February 2011, pp. 1–433.

  26. Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd international conference on embedded networked sensor systems (ser. SenSys ’04) (pp. 95–107). New York, NY, USA: ACM. Doi:10.1145/1031495.1031508

  27. Schurgers, C., Tsiatsis, V., Ganeriwal, S., & Srivastava, M. (2002). Optimizing sensor networks in the energy-latency-density design space. IEEE Transactions on Mobile Computing, 1(1), 70–80.

    Article  Google Scholar 

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

    Article  Google Scholar 

  29. Xiao, Y., Peng, M., Gibson, J., Xie, G., Du, D.-Z., & Vasilakos, A. (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 

  30. Li, Z., Das, A., Gupta, A., & Nandi, S. (2005). Full auto rate mac protocol for wireless ad hoc networks. IEE Proceedings Communications, 152(3), 311–319.

    Article  Google Scholar 

  31. Vutukuru, M., Balakrishnan, H., & Jamieson, K. (2009). Cross-layer wireless bit rate adaptation. SIGCOMM Computer Communication Review, 39(4), 3–14. Doi:10.1145/1594977.1592571

  32. Lacage, M., Manshaei, M. H., & Turletti, T. (2004). Ieee 802.11 rate adaptation: a practical approach. In Proceedings of the 7th ACM international symposium on modeling, analysis and simulation of wireless and mobile systems (ser. MSWiM ’04) (pp. 126–134). New York, NY, USA: ACM. Doi:10.1145/1023663.1023687

  33. Khan, S., Mahmud, S., & Al-Raweshidy, H. (2008). A rate-adaptive mac for ieee 802.11 networks. In 6th annual communication networks and services research conference, 2008 (CNSR 2008), pp. 463–469.

  34. Halperin, D., Greenstein, B., Sheth, A., & Wetherall, D. (2010). Demystifying 802.11n power consumption. In Proceedings of the 2010 international conference on Power aware computing and systems (ser. HotPower’10) (pp. 1). Berkeley, CA, USA: USENIX Association. http://dl.acm.org/citation.cfm?id=1924920.1924928

  35. Yin, W., Hu, P., Indulska, J., Portmann, M., & Guerin, J. (2012). Robust mac-layer rate control mechanism for 802.11 wireless networks. In IEEE 37th conference on local computer networks (LCN), 2012, pp. 419–427.

  36. Bandai, M., Maeda, S., & Watanabe, T. (2008). Energy efficient mac protocol with power and rate control in multi-rate ad hoc networks. In Vehicular technology conference, 2008. VTC Spring 2008 (pp. 66–70). IEEE.

  37. Ma, M., Zheng, J., Zhang, Y., Shao, Z., & Fujise, M. (2006). Wsn02-5: A power-controlled rate-adaptive mac protocol to support differentiated service in wireless ad hoc networks. In Global telecommunications conference, 2006 (GLOBECOM ’06) (pp. 1–5). IEEE.

  38. Chevillat, P., Jelitto, J., & Truong, H. L. (2005). Dynamic data rate and transmit power adjustment in ieee 802.11 wireless lans. International Journal of Wireless Information Networks, 12(3), 123–145. Doi:10.1007/s10776-005-0006-x

  39. Zhao, D., & Wang, Y. (2008). Sd-mac: Design and synthesis of a hardware-efficient collision-free qos-aware mac protocol for wireless network-on-chip. IEEE Transactions on Computers, 57(9), 1230–1245.

    Article  Google Scholar 

  40. Cheng, H. T., & Zhuang, W. (2009). Qos-driven mac-layer resource allocation for wireless mesh networks with non-altruistic node cooperation and service differentiation. IEEE Transactions on Wireless Communications, 8(12), 6089–6103.

    Article  Google Scholar 

  41. Jha, S., Phuyal, U., Rashid, M., & Bhargava, V. (2011). Design of omc-mac: An opportunistic multi-channel mac with qos provisioning for distributed cognitive radio networks. IEEE Transactions on Wireless Communications, 10(10), 3414–3425.

    Article  Google Scholar 

  42. Guevara, J., Barrero, F., Vargas, E., Becerra, J., & Toral, S. (2012). Environmental wireless sensor network for road traffic applications. IET Intelligent Transport Systems, 6(2), 177–186.

    Article  Google Scholar 

  43. Lee, U., Magistretti, E., Zhou, B., Gerla, M., Bellavista, P., & Corradi, A. (2006). Efficient data harvesting in mobile sensor platforms. In Fourth annual IEEE international conference on pervasive computing and communications workshops, 2006 (PerCom workshops 2006), March 2006, pp. 5, 356.

  44. Shannon, C. E., & Weaver, W. (1963). A mathematical theory of communication. Champaign, IL: University of Illinois Press.

    Google Scholar 

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Acknowledgments

This work is partially supported by NSERC-DIVA Strategic Research Network, Canada Research Chairs Program, and NSERC Research Funds.

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  1. PARADISE Research Laboratory, University of Ottawa, Ottawa, Canada

    Xiaoli Zhou & Azzedine Boukerche

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  1. Xiaoli Zhou
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Correspondence to Xiaoli Zhou.

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Zhou, X., Boukerche, A. A MAC transmission strategy in sparse Vehicular Delay-Tolerant Sensor Networks. Wireless Netw 21, 2237–2252 (2015). https://doi.org/10.1007/s11276-015-0910-7

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