Open Access

Energy-Efficient Medium Access Control Protocols for Wireless Sensor Networks

EURASIP Journal on Wireless Communications and Networking20062006:039814

DOI: 10.1155/WCN/2006/39814

Received: 3 November 2005

Accepted: 2 May 2006

Published: 18 June 2006

Abstract

A key challenge for wireless sensor networks is how to extend network lifetime with dynamic power management on energy-constraint sensor nodes. In this paper, we propose two energy-efficient MAC protocols: asynchronous MAC (A-MAC) protocol and asynchronous schedule-based MAC (ASMAC) protocol. A-MAC and ASMAC protocols are attractive due to their suitabilities for multihop networks and capabilities of removing accumulative clock-drifts without any network synchronization. Moreover, we build a traffic-strength- and network-density-based model to adjust essential algorithm parameters adaptively. Simulation results show that our algorithms can successfully acquire the optimum values of power-on/off duration, schedule-broadcast interval, as well as super-time-slot size and order. These algorithm parameters can ensure adequate successful transmission rate, short waiting time, and high energy utilization. Therefore, not only the performance of network is improved but also its lifetime is extended when A-MAC or ASMAC is used.

[12345678910111213141516171819202122232425262728293031323334353637]

Authors’ Affiliations

(1)
Department of Electrical Engineering, The University of Texas at Arlington

References

  1. Culler D, Estrin D, Srivastava M: Guest Editors' Introduction: overview of sensor networks. Computer 2004,37(8):41–49.View ArticleGoogle Scholar
  2. Zhao F, Guibas L: Wireless Sensor Networks: An Information Processing Approach. Morgan Kaufmann, San Francisco, Calif, USA; 2004.Google Scholar
  3. Stemm M, Katz RH: Measuring and reducing energy consumption of network modules in hand-held devices. IEICE Transactions on Communications 1997,E80-B(8):1125–1131.Google Scholar
  4. Chou J, Petrovic D, Ramachandran K: A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks. Proceedings of 22nd Annual Joint Conference on the IEEE Computer and Communications Societies (INFOCOM '03), March-April 2003, San Francisco, Calif, USA 2: 1054–1062.Google Scholar
  5. Chebolu ML, Veeramachaneni VK, Jayaweera SK, Namuduri KR: An improved adaptive signal processing approach to reduce energy consumption in sensor networks. Proceedings of 38th Annual Conference on Information Science and System (CISS '04), March 2004, Princeton, NJ, USAGoogle Scholar
  6. Balasubramanian S, Elangovan I, Jayaweera SK, Namuduri KR: Distributed and collaborative tracking for energy-constrained ad-hoc wireless sensor networks. Proceedings of IEEE Wireless Communications and Networking Conference (WCNC '04), March 2004, Atlanta, Ga, USA 3: 1732–1737.Google Scholar
  7. Jayaweera SK: An energy-efficient virtual MIMO communications architecture based on V-BLAST processing for distributed wireless sensor networks. Proceedings of 1st Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON '04), October 2004, Santa Clara, Calif, USA 299–308.Google Scholar
  8. Elson JE: Time synchronization in wireless sensor networks, Dissertation. Computer Science Department, University of California Los Angeles, Los Angeles, Calif, USA; 2003.Google Scholar
  9. Ma C, Ma M, Yang Y: Data-centric energy efficient scheduling for densely deployed sensor networks. Proceedings of IEEE International Conference on Communications, June 2004, Paris, France 6: 3652–3656.Google Scholar
  10. Singh S, Raghavendra CS: Pamas: power aware multi-access protocol with signaling for ad hoc networks. ACM SIGCOMM Computer Communication Review 1998,28(3):5–26. 10.1145/293927.293928View ArticleGoogle Scholar
  11. P802.11 : Ieee standard for wireless lan medium access control (mac) and physical layer (phy) specifications. November 1997
  12. Hill JL, Culler DE: Mica: a wireless platform for deeply embedded networks. IEEE Micro 2002,22(6):12–24. 10.1109/MM.2002.1134340View ArticleGoogle Scholar
  13. Rajendran V, Obraczka K, Garcia-Luna-Aceves JJ: Energy-efficient, collision-free medium access control for wireless sensor networks. Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys '03), November 2003, Los Angeles, Calif, USA 181–192.View ArticleGoogle Scholar
  14. van Hoesel LFW, Nieberg T, Kip HJ, Havinga PJM: Advantages of a TDMA based, energy-efficient, self-organizing MAC protocol for WSNs. Proceedings of IEEE 59th Vehicular Technology Conference (VTC '04), May 2004, Milan, Italy 3: 1598–1602.Google Scholar
  15. Li J, Lazarou GY: A bit-map-assisted energy-efficient MAC scheme for wireless sensor networks. Proceedings of 3rd International Symposium on Information Processing in Sensor Networks (IPSN '04), April 2004, Berkeley, Calif, USA 55–60.Google Scholar
  16. Biaz S, Barowski YD: GANGS: an energy efficient MAC protocol for sensor networks. Proceedings of the 42nd Annual Southeast Regional Conference (ACMSE '04), April 2004, Huntsville, Ala, USA 82–87.View ArticleGoogle Scholar
  17. Ye W, Heidemann J, Estrin D: An energy-efficient MAC protocol for wireless sensor networks. Proceedings of 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '02), June 2002, New York, NY, USA 3: 1567–1576.Google Scholar
  18. Van Dam T, Langendoen K: An adaptive energy-efficient MAC protocol for wireless sensor networks. Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys '03), November 2003, Los Angeles, Calif, USA 171–180.View ArticleGoogle Scholar
  19. Polastre J, Hill J, Culler D: Versatile low power media access for wireless sensor networks. Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys '04), November 2004, Baltimore, Md, USA 95–107.View ArticleGoogle Scholar
  20. Jayashree S, Manoj BS, Murthy CSR: On using battery state for medium access control in ad hoc wireless networks. Proceedings of the 10th Annual International Conference on Mobile Computing and Networking (MobiCom '04), September-October 2004, Philadelphia, Pa, USA 360–373.View ArticleGoogle Scholar
  21. Jung E-S, Vaidya NH: A power control MAC protocol for ad hoc networks. Proceedings of the 8th Annual International Conference on Mobile Computing and Networking (MobiCom '02), September 2002, Atlanta, Ga, USA 36–47.View ArticleGoogle Scholar
  22. Bregni S: Synchronization of Digital Telecommunications Networks . John Wiley & Sons, New York, NY, USA; 2002.View ArticleGoogle Scholar
  23. Cristian F: Probabilistic clock synchronization. Distributed Computing 1989,3(3):146–158. 10.1007/BF01784024MATHView ArticleGoogle Scholar
  24. Gusella R, Zatti S: The accuracy of the clock synchronization achieved by TEMPO in Berkeley UNIX 4.3 BSD. IEEE Transactions on Software Engineering 1989,15(7):847–853. 10.1109/32.29484View ArticleGoogle Scholar
  25. Srikanth TK, Toueg SK: Optimal clock synchronization. Journal of the ACM 1987,34(3):626–645. 10.1145/28869.28876MathSciNetView ArticleGoogle Scholar
  26. Su W, Akyildiz IF: Time-diffusion synchronization protocol for wireless sensor networks. IEEE/ACM Transactions on Networking 2005,13(2):384–397.View ArticleGoogle Scholar
  27. Mendel JM: Fuzzy logic systems for engineering: a tutorial. Proceedings of the IEEE 1995,83(3):345–377. 10.1109/5.364485View ArticleGoogle Scholar
  28. Mamdani EH: Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Transactions on Computers 1977,26(12):1182–1191.MATHView ArticleGoogle Scholar
  29. Mendel JM: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper Saddle River, NJ, USA; 2001.Google Scholar
  30. Altrock CV: Fuzzy logic design: methodology, standards, and tools. Electronic Engineering Times July 1996.Google Scholar
  31. Bao LH, Garcia-Luna-Aceves JJ: Hybrid channel access scheduling in ad hoc networks. Proceedings of 10th IEEE International Conference on Network Protocols (ICNP '02), November 2002, Paris, France 46–57.Google Scholar
  32. Bertsekas D, Gallager R: Data Networks. Prentice-Hall, Upper Saddle River, NJ, USA; 1987.Google Scholar
  33. Carvalho MM, Garcia-Luna-Aceves JJ: Delay analysis of IEEE 802.11 in single-hop networks. Proceedings of 11th IEEE International Conference on Network Protocols (ICNP '03), November 2003, Atlanta, Ga, USA 146–155.Google Scholar
  34. Bianchi G: Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications 2000,18(3):535–547. 10.1109/49.840210View ArticleGoogle Scholar
  35. Manjeshwar A, Zeng Q-A, Agrawal DP: An analytical model for information retrieval in wireless sensor networks using enhanced APTEEN protocol. IEEE Transactions on Parallel and Distributed Systems 2002,13(12):1290–1302. 10.1109/TPDS.2002.1158266View ArticleGoogle Scholar
  36. Mhatre VP, Rosenberg C, Kofman D, Mazumdar R, Shroff N: A minimum cost heterogeneous sensor network with a lifetime constraint. IEEE Transactions on Mobile Computing 2005,4(1):4–14.View ArticleGoogle Scholar
  37. Heinzelman WB, Chandrakasan AP, Balakrishnan H: An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications 2002,1(4):660–670. 10.1109/TWC.2002.804190View ArticleGoogle Scholar

Copyright

© Q. Ren and Q. Liang 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement