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Low Duty Cycle, Energy-Efficient and Mobility-Based Boarder Node—MAC Hybrid Protocol for Wireless Sensor Networks

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Abstract

The need for an efficient medium access control (MAC) protocol is extremely important with the emergence of wireless sensor networks (WSNs). The MAC protocol has increasingly been significant in advancing the performance of WSNs. In this paper, a low duty cycle, energy-efficient and mobility-based Boarder Node Medium Access Control (BN-MAC) hybrid protocol is introduced for WSNs that controls overhearing, idle listening and congestion issues by preserving energy over WSNs. BN-MAC leverages the features of contention and schedule-based MAC protocols. The contention encompasses the novel semi-synchronous approach that helps obtain faster access to the medium. The schedule-based part helps reduce the collision and overhearing problems.

The idle listening control (ILC) model is embedded within the BN-MAC that administers the nodes to go to sleep after performing their tasks to saves additional energy. The least distance smart neighboring search (LDSNS) model is used to determine the shortest and most efficient path in a one-hop neighborhood.

Evaluation of the BN-MAC is conducted using network simulator-2 (ns2), then its quality of service (QoS) parameters are compared with other known hybrid MAC protocols including X-MAC, Zebra medium access control (Z-MAC), mobility-aware SMAC (MS-MAC), advertisement-based MAC (A-MAC), Adaptive Duty Cycle SMAC (ADC-SMAC) and Mobile Sensor (MobiSense) MAC protocols.

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Notes

  1. 1.

    A weighted greedy algorithm: It can be considered as backtracking algorithm where each decision point “the best” selection is already known and accordingly can be chosen without having to think over any of the substitute.

  2. 2.

    Semi-synchronous: This feature is desirable for decreasing latency and energy consumption for several WSN application areas to improve the throughput.

  3. 3.

    Anycast communication: It is message mechanism that only sends control message to the nearest node within the group of possible receivers or may pick several nodes with subject to condition.

  4. 4.

    Short preamble: It is used to make the receiver to be ready that data is on its way. In addition, it is also first portion of the Physical layer Convergence Protocol/Procedure (PLCP) Protocol Data Unit (PDU). The short preamble lets the receiver to get the wireless signal and coordinate itself with the transmitter.

  5. 5.

    Promiscuous mode: It causes the controller to permit all traffic rather than allowing only the frames. Promiscuous mode is also used to detect network connectivity problems.

  6. 6.

    Relative Standard Deviation (RSD): It is the absolute value for deviation of coefficient and defined as a percentage. It is also commonly used when doing quality assurance.

  7. 7.

    Gini coefficient: It is an inequality distribution measure that is expressed as the ratio with values between 0 and 1.

References

  1. 1.

    Meng, W., Xie, L., & Xiao, W. (2013). Optimality Analysis of Sensor-Source Geometries in Heterogeneous Sensor Networks. IEEE Transaction on Wireless Communications, 12(4), 1958–1967.

  2. 2.

    Razaque, A., & Elleithy, K. M. (2012). Automated Energy Saving (AES) Paradigm to Support Pedagogical Activities over Wireless Sensor Networks. In lecture notes in In Proceedings of the 6th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI), Vitoria-Gasteiz, Spain, 3–5 December 2012. In Lecture notes in computer science 7656 (pp. 512–519). Berlin/Heidelberg: Springer. doi:10.1007/978-3-642-35377-2_70.

  3. 3.

    Joshi, Y.K., Younis, M. (2012). Autonomous recovery from multi-node failure in Wireless Sensor Network. In proceedings of the IEEE international conference on Global Communications (GLOBECOM),(pp. 652-657).Anaheim.

  4. 4.

    Wu, W. Y., Li, Y. X., LI, M., & Lou, W. (2010). Energy-efficient wake-up scheduling for data collection and aggregation. IEEE Transaction on Parallel and Distributed System, 21(2), 275–287.

  5. 5.

    Hao, J., Govindan, R. (2003).Understanding packet delivery performance in dense wireless sensor networks. In proceedings of the 1st international conference on Embedded networked sensor systems, (pp.1-13), Los Angeles, CA, ACM, November 5-7, 2003.doi: 10.1145/958491.958493.

  6. 6.

    Reddy, S., Samanta, V., Burke, J., Estrin, D., Hansen, M., Srivastava, M.(2009) MobiSense - Mobile Network Services for Coordinated Participatory Sensing. In Proceedings of IEEE 9th International Symposium on Autonomous Decentralized Systems (ISADS), (pp.1-6), Athens. doi: 10.1109/ISADS.2009.5207328.

  7. 7.

    Wu, C., Zhang, Y., Sheng, W., & Kanchi, S. (2010). Rigidity guided localization for mobile robotic sensor networks. International. Journal of Ad Hoc and Ubiquitous Computing, 6(2), 114–128.

  8. 8.

    Rhee, I., Warrier, A., Aia, M., Min, J., & Sichitiu, M. L. (2008). ZMAC: a hybrid MAC for wireless sensor networks. IEEE/ACM Transcations on Networking, 16(3), 511–524.

  9. 9.

    Kyle Jamieson, K., Balakrishnan, H., Tay, C.Y. (2006). Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks. In proceedings of the third European Workshop on wireless sensor networks (EWSN), Zurich, Switzerland. In lecture Notes in Computer Science 3868 (pp. 260–275). doi: 10.1007/11669463_20.

  10. 10.

    Razaque, A., & Elleithy, K. M. (2013). Automatic energy saving (AES) model to boost ubiquitous wireless sensor networks (WSNs). International Journal of computers and technology (IJCT), 10(5), 1640–1645.

  11. 11.

    Ahmed, N.B., Senouci, S., Ghamri-Doudane, Y., Beylot, A.L. (2011). A Cooperative Low Power MAC Protocol for Wireless Sensor Networks. In proceedings of IEEE International Conference on Communications (ICC),(pp.1-6). Kyoto.doi: 10.1109/icc.2011.5962416.

  12. 12.

    Shi, L., & Fapojuwo, A. (2010). TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks. IEEE Transactions on Mobile Computing, 9(7), 927–939.

  13. 13.

    Wong, J.K., Arvind, D.K. (2006). Low Power Decentralized MAC Protocols for Low Data Rate Transmissions in Specknets”, In Proceedings of ACM International Workshop on Multihop Ad-hoc Networks: From Theory to Reality, (pp.1-9), Florence, Italy. doi: 10.1145/1132983.1132996.

  14. 14.

    Buettner, M., Yee, V.G., Anderson, E., Han.R.(2006).X-MAC: A Short Preamble MAC Protocol for Duty-Cycled Wireless Sensor Networks. In proceedings of the ACM 4th international conference on embedded networked sensor systems SenSys-06, (pp.307-320), Boulder, Colorado, USA. doi: 10.1145/1182807.1182838.

  15. 15.

    Pham, H., Jha, S.(2004).An adaptive mobility-aware mac protocol for sensor networks (MS-MAC).In proceedings of IEEE International Conference on Mobile Ad-hoc and Sensor Systems,(pp. 558 – 560), doi: 10.1109/MAHSS.2004.1392207.

  16. 16.

    Hideyuki, N., Hamid, A., Carlos, J.A.(2010). Handbook on Ambient Intelligence and Smart Environments. Springer, doi: 10.1007/978-0-387-93808-0.

  17. 17.

    Bellavista, P., Montanari, R., & Das, K. S. (2013). Mobile social networking middleware:A survey. International Journal Elsevier for Pervasive and Mobile Computing, 9(4), 437–453.

  18. 18.

    EkbataniFard, G., Monsefi, R.(2011). A Multi-channel Asynchronous MAC Protocol for Wireless Sensor Networks. In proceedings of IEEE 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, (pp. 91-98), Barcelona. doi: 10.1109/BWCCA.2011.18.

  19. 19.

    Ziqiang, A. (2012). Medium access control protocol with dynamic duty cycle in wireless sensor network. International Journal of Future Computer and Communication, 1(1), 36–39.

  20. 20.

    Ye, W., Heidemann, J., Estrin, D. (2002). An Energy-Efficient MAC Protocol for Wireless Sensor Networks”, In Proceedings of the 21st International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2002), (pp. 1567 – 1576), New York, NY, USA. doi: 10.1109/INFCOM.2002.1019408.

  21. 21.

    Ali, M., Suleman, T., Uzmi, Z.A. A Mobility Adaptive, Collision Free MAC Protocol for Wireless Sensor Networks. In proceedings of the 24th IEEE international conference on Performance, Computing, and Communications (IPCCC), (pp. 401 – 407), Phoenix, Arizona, USA.doi: 10.1109/PCCC.2005.1460597.

  22. 22.

    Afonso, J.A., Rocha, L.A., Silva, H.R., Correia, J.H.(2006). MAC Protocol for Low-Power Real-Time Wireless Sensing and Actuation. In proceedings of In Proc. of the 11th IEEE International Conference on Electronics, Circuits and Systems, (pp.1248-1251), Nice. doi: 10.1109/ICECS.2006.379688.

  23. 23.

    Yahya, B., Othman, B.J. (2009).An adaptive mobility aware and energy efficient MAC protocol for wireless sensor networks. In proceedings of IEEE symposium on communication, (pp.15-21), Sousse.doi: 10.1109/ISCC.2009.5202382.

  24. 24.

    Liang, L., Liu, X., Wang, Y., Feng, W., Yang, G. SW-MAC: A Low-Latency MAC Protocol with Adaptive Sleeping for Wireless Sensor Networks. International Journal Springer on Wireless Personal Communications. US.doi: 10.1007/s11277-013-1561-6.

  25. 25.

    Ko, J., Lim, H., Chen, J., Musaloiu-e, R., Terzis, A., Masson, M. G., Gao, T., et al. (2010). BMEDiSN: medical emergency detection in sensor networks. ACM Transactions on Embedded Computing Systems, 10(1), 1–28.

  26. 26.

    Hoag Memorial Hospital Presbyterian, Newport Beach, CA. http://www.hoag.org/Locations/Pages/Hoag-Hospital-Newport-Beach.aspx. Accessed 20 March 2014.

  27. 27.

    Razaque, A., & Elleithy, K. M. (2014). Energy-efficient boarder node medium access control protocol for wireless sensor networks. Sensors, 14(3), 5074–5117.

  28. 28.

    Tezcan, N., Wang, W., Chow, Y.M. A bidirectional reliable transport mechanism for wireless sensor networks”, In proceedings of IEEE international conference for Military Communications MILCOM, (pp.1193-1199), Atlantic City, NJ, USA. doi: 10.1109/MILCOM.2005.1605840.

  29. 29.

    Razaque A., Elleithy. K. M. (2013). Least distance smart neighboring search (LDSNS) over wireless sensor networks. In: Proceeding of IEEE international conference on European modelling symposium EMS2013, (pp. 549 – 554), Manchester, United Kingdom. doi: 10.1109/EMS.2013.91.

  30. 30.

    Razaque, A., Elleithy, K. M. (2014). Pheromone Termite (PT) Model to provide Robust Routing over WSNs. In Proceedings of the IEEE International Conference for American Society for Engineering Education (ASEE), Bridgeport, CT, USA, 3–5 April 2014.

  31. 31.

    Lin, J., Ingram, A.M. (2012). SCT-MAC: A Scheduling Duty Cycle MAC protocol for Cooperative Wireless Sensor Network. In proceedings of IEEE ICC2012 Ad-hoc and sensor networking symposium, (pp. 345-349), Ottawa, ON. Doi: 10.1109/ICC.2012.6364580.

  32. 32.

    Razaque, A., Elleithy, M.K. Mobility-Aware Hybrid Medium Access Control Protocol for Wireless Sensor Network (WSN). In Proceedings of the 2014 I.E. Sensors Applications Symposium, Rydges Lakeland Resort, Queenstown, New Zealand, 18–20 February 2014.

  33. 33.

    Dargie, W., Poellabauer, C. (2011). Fundamentals of Wireless Sensor Networks: Theory and Practice. Wiley Series on Wireless Communications and Mobile Computing. January 10, 2011

  34. 34.

    Benmansour, T., & Moussaoui, S. (2011). GMAC: Group mobility adaptive clustering scheme for Mobile Wireless Sensor Networks. In proceedings of 10th International Symposium on Programming and Systems (ISPS), (pp.67-73), Algiers. doi: 10.1109/ISPS.2011.5898886.

  35. 35.

    Itzel, L., Heger, F., Schiele, G., Becker, C.(2011).The quest for meaningful mobility in massively multi-user virtual environments. In proceedings of the 10th Annual workshop on network and Systems Support for Games (NetGames), (pp. 1-2), Ottawa, ON. doi: 10.1109/NetGames.2011.6080991.

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Correspondence to Abdul Razaque.

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Razaque, A., Elleithy, K.M. Low Duty Cycle, Energy-Efficient and Mobility-Based Boarder Node—MAC Hybrid Protocol for Wireless Sensor Networks. J Sign Process Syst 81, 265–284 (2015). https://doi.org/10.1007/s11265-014-0947-3

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Keywords

  • Wireless sensor networks
  • Medium access control protocols
  • Energy efficiency
  • Mobility
  • Handling mass casualties