Efficient Mac Protocols For Wireless Sensor Networks



This paper proposes a MAC protocol for Radio Frequency (RF) energy harvesting in Wireless Sensor Networks (WSN). In the conventional RF energy harvesting methods, an Energy Transmitter (ET) operates in a passive manner. An ET transmits RF energy signals only when a sensor with depleted energy sends a Request-for-Energy (RFE) message. Unlike the conventional methods, an ET in the proposed. Sensor networks they are secondary. This paper presents sensor-MAC (S-MAC), a new MAC pro-tocol explicitly designed for wireless sensor networks. While reducing energy consumption is the primary goal in our design, our protocol also has good scalability and collision avoidance capability. It achieves good scalability and collision avoidance. MAC protocols in wireless sensor networks play an important rule in energy consumption. In this paper, we first show that the properties of sensor network and its different with other wireless.

Sensor Media Access Control(S-MAC) is a network protocol for sensor networks. Sensor networks consist of tiny, wirelessly communicating computers (sensor nodes), which are deployed in large numbers in an area to network independently and as long as monitor their surroundings in group work with sensors, to their energy reserves are depleted. A special form of ad hoc network, they make entirely different demands on a network protocol (for example, the Internet) and therefore require specially for them developed network protocols. Sensor Media Access Control specifies in detail how the nodes of a sensor network exchange data, controls the Media Access Control (MAC) to access the shared communication medium of the network, regulates the structure of the network topology, and provides a method for synchronizing.

She is currently performing research in the area of wireless sensor networks at Ramanujan Computing Centre, Anna University, Chennai, India. Her areas of interest include wireless ad hoc networking, sensor networks, and energy‐efficient MAC protocols.

Although today primarily of academic interest, S-MAC was a significant step in sensor network research and inspired many subsequent network protocols. It was introduced in 2001 by Wei Ye, John Heidemann and Deborah Estrin of the University of Southern California and was intended to conserve scarce, non-rechargeable energy resources of sensor nodes.[1] The development was supported financially by the US military agency DARPA under the project Sensor Information Technology (Sensit).

Efficient Mac Protocols For Wireless Sensor Networks

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  1. ^Ye, Wei; Heidemann, J.; Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE. 3. pp. 1567–1576. CiteSeerX10.1.1.16.1535. doi:10.1109/INFCOM.2002.1019408. ISBN978-0-7803-7476-8.
Efficient Mac Protocols For Wireless Sensor Networks


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Efficient Mac Protocols For Wireless Sensor Networks Wireless

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An Adaptive Energy-efficient Mac Protocol For Wireless Sensor Networks

  1. Sung, W., Wu, T.-T., Yang, C.-S., Huang, Y.-M.: Reliable data broadcast for Zigbee wireless sensor networks. Int. J. Smart Sensing Intell. Syst. 3(3) (2010)Google Scholar
  2. Jang, W.S., Healy, W.M.: Assessment of performance metrics for use of WSNs in buildings. In: International Symposium on Automation and Robotic in Construction (ISARC 2009), 27–29 June 2009, pp. 570–575 (2009)Google Scholar
  3. Mouftah, H.T., Khanafer, M., Guennoun, M.: Wireless sensor network architectures for intelligent vehicular systems. In: Symposium International for Telecommunication Techniques (2010)Google Scholar
  4. Suh, C., Mir, Z.H., Ko, Y.-B.: Design and implementation of enhanced IEEE 802.15.4 for supporting multimedia service in wireless sensor networks. Int. J. Comput. Telecommun. Netw. 52(13), 2568–2581 (2008)CrossRefGoogle Scholar
  5. Golmie, N., Cypher, D., Rebala, O.: Performance analysis of low rate wireless technologies for medical applications. J. Comput. Commun. 28(10), 1266–1275 (2005). ISSN 0140-3664CrossRefGoogle Scholar
  6. Zhoul, H., Chen, X., Liu, X., Yang, J.: Applications of Zigbee wireless technology tomeasurement system in grain storage. In: Computer and Computing Technologies in Agriculture II. IFIP International Federation for Information Processing, vol. 3, pp. 2021–2029 (2009). https://doi.org/10.1007/978-1-4419-0213-952
  7. Willig, A.: Recent and emerging topics in wireless industrial communication. IEEE Trans. Industr. Inf. 4(2), 102–124 (2008)CrossRefGoogle Scholar
  8. Lecointre, A., Berthe, A., Dragomirescu, D., Plana, R.: Performance evaluation of impluse radio ultra wide band wireless sensor networks. In: Proceedings of the 28th IEEE Conference on Military Communications, MILCOM 2009, pp. 1191–1197 (2009)Google Scholar
  9. Amundson, I., Koutsoukos, X., Sallai, J.: Mobile sensor localization and navigation using RF doppler shifts. In: 1st ACM International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2008 (2008)Google Scholar
  10. Fang, L., Antsaklis, P.J., Montestruque, L., Mcmickell, M.B., Lemmon, M., Sun, Y., Fang, H., Koutroulis, I., Haenggi, M., Xie, M., Xie, X.: Design of a wireless assisted pedestrian dead reckoning system – the NavMote experience. IEEE Trans. Instrum. Meas. 54(6), 2342–2358 (2005)CrossRefGoogle Scholar
  11. Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L., Rubenstein, D.: Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet. In: Proceedings of ASPLOS-X (2002)Google Scholar
  12. Kusy, B., Ledeczi, A., Koutsoukos, X.: Tracking mobile nodes using RF doppler shifts. In: Proceedings of the 5th International Conference on Embedded Networked Sensor Systems, SenSys 2007, pp. 29–42. ACM, New York (2007)Google Scholar
  13. Dutta, P., Grimmer, M., Arora, A., Bibyk, S., Culler, D.: Design of a wireless sensor network platform for detecting rare, random, and ephemeral events. In: Proceedings of IPSN/SPOTS, April 2005Google Scholar
  14. Polastre, J., Szewczyk, R., Culler, D.: Telos: enabling ultra-low power wireless research. In: Proceedings of IPSN/SPOTS, April 2005Google Scholar
  15. Dantu, K., Rahimi, M., Shah, H., Babel, S., Dhariwal, A., Sukhatme, G.S.: Robomote: enabling mobility in sensor networks. In: The Fourth International Symposium on Information Processing in Sensor Networks, IPSN 2005 (2005)Google Scholar
  16. Friedman, J., Lee, D.C., Tsigkogiannis, I., Wong, S., Chao, D., Levin, D., Kaisera, W.J., Srivastava, M.B.: Ragobot: a new platform for wireless mobile sensor networks. In: International Conference on Distributed Computing in Sensor Systems, DCOSS 2005 (2005)Google Scholar
  17. Bergbreiter, S., Pister, K.S.J.: CotsBots: an off-the-shelf platform for distributed robotics. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2003 (2003)Google Scholar
  18. Shah, R., Roy, S., Jain, S., Brunette, W.: Data mules: modeling a three-tier architecture for sparse sensor networks. In: Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications (2003)Google Scholar
  19. Wang, G., Cao, G., Porta, T., Zhang, W.: Sensor relocation in mobile sensor networks. In: IEEE INFOCOM 2005 (2005)Google Scholar
  20. Lazaro, A., Girbau, D., Villarino, R.: Analysis of vital signs monitoring using an IR-UWB radar. Prog. Electromagnet. Res. 100, 265–284 (2010)CrossRefGoogle Scholar
  21. Adsul, A.P., Bodhe, S.K.: Performance comparison of BPSK, PPM and PPV modulation based IR-UWB receiver using wide band LNA. Int. J. Comput. Technol. Appl. 3(4), 1532–1537 (2012)Google Scholar
  22. Piguet, D., Decotignie, J.-D., Rousselot, J.: A MAC protocol for micro flying robots coordination. European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no 231855 (sFly)Google Scholar
  23. Rousselot, J., El-Hoiydi, A., Decotignie, J.-D.: WideMac: simple and efficient medium access for UWB sensor networks. In: IEEE International Conference on Ultra-Wideband (2008)Google Scholar
  24. Sun, Y., Gurewitz, O., Johnson, D.B.: RI-MAC: a receiver- initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, SenSys 2008, pp. 1–14. ACM, New York (2008)Google Scholar
  25. Köpke, A., Swigulski, M., Wessel, K., Willkomm, D., Klein Haneveld, P.T., Parker, T.E.V., Visser, O.W., Lichte, H.S., Valentin, S.: Simulating wireless and mobile networks in OMNeT++ the MiXiM vision. In: Proceedings of International Workshop on OMNeT++ (co-located with SIMUTools 2008), March 2008Google Scholar