Medium Access Control Based on Adaptive Sleeping and Probabilistic Routing for Delay Tolerant Mobile Sensor Networks

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The paper proposes a medium access control (MAC) scheme with coordinated and adaptive wakeup scheme designed for delay tolerant mobile sensor networks (DTMSNs). Many applications motivate MAC schemes for DTMSNs that are different from traditional wireless MAC such as IEEE 802.15.4 in several ways: energy conservation and average delay. MAC with coordinated and adaptive wakeup scheme protocol uses a few novel techniques to reduce energy consumption and message overhead rates. It can reduce significantly control overhead and adaptively wake up, and it avoids overhearing unnecessary traffic. Finally, in this paper, simulation applies message passing to reduce contention latency for applications that require in-network data processing. Simulation results show that MAC with Adaptive Sleeping and based on Probabilistic Routing protocol (MAC-ASPR) obtains significant energy savings compared with IEEE 802.15.4 and S-MAC.

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821-829

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October 2013

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] K. Fall, A Delay-Tolerant Network Architecture for Challenged Internets, in Proc. SIGCOMM (2003).

Google Scholar

[2] Wei Ye, Medium Access Control With Coordinated Adaptive Sleeping for Wireless Sensor Networks, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 12, NO. 3, JUNE (2004).

DOI: 10.1109/tnet.2004.828953

Google Scholar

[3] Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, IEEE Std. 802. 15. 4 edition.

Google Scholar

[4] Lu, G., B. Krishnamachari, and C. S. Raghavendra. April 2004. Performance Evaluation of the IEEE 802. 15. 4 MAC for Low-Rate Wireless Networks. " In Proceedings of the IEEE International Performance Computing and Communication Conference (IPCCC, 04), 701–6. Phoenix, AZ.

DOI: 10.1109/pccc.2004.1301180

Google Scholar

[5] Woon, W. T. H., and T. C. Wan. 2008. Performance Evaluation of IEEE 802. 15. 4 Wireless Multi-Hop Networks: Simulation and Testbed Approach., International Journal of Ad-Hoc and Ubiquitous Computing 3 (1): 57–66.

DOI: 10.1504/ijahuc.2008.016195

Google Scholar

[6] G. J. Pottie and W. J. Kaiser, Embedding the internet: Wireless integrated network sensors, Commun. ACM, vol. 43, no. 5, p.51–58, May (2000).

DOI: 10.1145/332833.332838

Google Scholar

[7] C. Intanagonwiwat, R. Govindan, and D. Estrin, Directed diffusion: A scalable and robust communication paradigm for sensor networks, in Proc. ACM/IEEE Int. Conf. Mobile Computing and Networking, Boston, MA, Aug. 2000, p.56–67. M.

DOI: 10.1145/345910.345920

Google Scholar

[8] Wei Ye, J. Heidemann, and D. Estrin, An Energy-efficient MAC Protocol for Wireless Sensor Networks, Proc. IEEE INFOCOM 2002, (Jun. 2002), p.1567–1576.

DOI: 10.1109/infcom.2002.1019408

Google Scholar

[9] X. Guo, M. R. Frater, and M. J. Ryan, A propagation-delay-tolerant collision avoidance protocol for underwater acoustic sensor networks, " in Proc. MTS/IEEE OCEANS, 06, (2006).

DOI: 10.1109/oceansap.2006.4393849

Google Scholar

[10] N. Chirdchoo, W. S. Soh, and K. C. Chua, MACA-MN: a MAC based MAC protocol for underwater acoustic networks with packet train for multiple neighbors, in Proc. VTC, (2008).

DOI: 10.1109/vetecs.2008.22

Google Scholar

[11] Fu Kai, Sleep Scheme Based on Contact Time in DTN, Computer Science, 2013. 2(40), 87-90.

Google Scholar

[12] A. Lindgren, A. Doria, O. Schelen, Probabilistic Routing in Intermittently Connected Networks, Lecture Notes in Computer Science, Vol. 3126 (January 2004), pp.239-254.

DOI: 10.1007/978-3-540-27767-5_24

Google Scholar

[13] Hameed, S. A., E. M. Shaaban, H. M. Faheem, and M. S. Ghoniemy. October 2009 Mobility-Aware MAC Protocol for Delay Sensitive Wireless Sensor Networks., In IEEE Ultra Modern Telecommunications Workshops, 2009, 1–8.

DOI: 10.1109/icumt.2009.5345591

Google Scholar

[14] CHAN C Y M,MEHUL M.An integrated energy efficient data retrieval protocol for underwater delay tolerant networks, IEEE OCEANS.Washington,DC:IEEE Press,2007:1—6.

DOI: 10.1109/oceanse.2007.4302341

Google Scholar

[15] H. Mohamed, M. H. Lee, M. Sarahintu, S. Salleh and B. Sanugi, Identifying Factors Affecting Data Delivery Performance in Mobile Ad-hoc Network Routing Protocol Using a Systematic Approach, J. Matematika, 24(1), 2008, pp.43-51.

DOI: 10.3844/jmssp.2008.194.198

Google Scholar

[16] P. Juang, H. Oki, Y. Wang, et al. Energy-Efficient Computing for Wildlife Tracking: Design Tradeos and Early Experiences with ZebraNet. In Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), Oct. 2002. pp.201-221.

DOI: 10.1145/605397.605408

Google Scholar

[17] R. Kling. Intel Mote: An Enhanced Sensor Network Node. In International Workshop on Advanced Sensors, Structural Health Monitoring, and Smart Structures, Nov. (2003).

Google Scholar

[18] K. Langendoen and N. Reijers. Distributed Localization in Wireless Sensor Networks: a Quantitative Comparison. Computer Networks: The International Journal of Computer and Telecommunications Networking, 43(4): 499-518, (2003).

DOI: 10.1016/s1389-1286(03)00356-6

Google Scholar

[19] lan F. Akyildiz and Mehmet Can Vuran, Wirless Sensor Networks, 1st edition, pp.84-89, Oct. (2010).

Google Scholar

[20] M. Mauve, J. Widmer, and H. Hartenstein. A Survey on Position Based Routing in Mobile Ad-Hoc Networks. IEEE Network Magazine 15 (6), pp.30-39, Nov. (2001).

DOI: 10.1109/65.967595

Google Scholar