Minimizing Single TDMA Frame Sizes in Alarm-driven Wireless Sensor Networks Applications

  • Mário Macedo
  • Mário Nunes
  • António Grilo
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 284)

Energy-efficiency and latency requirements in alarm-driven Wireless Sensor Networks often demand the use of TDMA protocols with special features such as cascading of timeslots, in a way that the sensor-to-sink delay bound can stay below a single frame. However, this single TDMA frame should be as small as possible. This paper presents a comparative study of timeslot allocation strategies that can be used to attain this goal. The Minimum Single Frame Size Problem is formulated, and the considered slot allocation algorithms are studied based on simulations. The results point to the conclusion that informed depth-first, coupled with a longest-path-first heuristic, can improve significantly the behavior of blind depth-first. Two centralized strategies are also simulated: a longest-paths-first, which allocates the branches by decreasing order of the length of the paths, and a largest-distances-first, which allocates the branches by decreasing distances to the sink that the paths can reach. It is also shown that a largest-distances-first strategy can achieve the smallest single frame sizes, and also the lowest variation of frame sizes. A distributed version of this algorithm (DIST-LDF) is presented, which obtains the same results of its centralized version.


Wireless Sensor Network Sink Node Frame Size Interference Range Slot Allocation 


  1. 1.
    G. Lu, B. Krishnamachari, C. S. Raghavendra, “An Adaptive Energy-Efficient and LowLatency MAC for Data Gathering in Wireless Sensor Networks”, in Proceedings of the 18th International Parallel and Distributed Processing Symposium (IPDPS 2004), Santa Fe, NM, USA, April 2004.Google Scholar
  2. 2.
    I. Chlamtac, S. Kutten; “Tree-based Broadcasting in Multihop Radio Networks”, IEEE Transactions on Computers, Volume C-36, No. 10, Oct. 1987.Google Scholar
  3. 3.
    I. Rhee, A. Warrier, J. Min, L. Xu, “DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad-hoc Networks”, the 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc’2006), Florence, Italy, May 2006.Google Scholar
  4. 4.
    V. Annamalai, S.K.S. Gupta, L. Schwiebert, “On Tree-Based Convergecasting in Wireless Sensor Networks”, in the Proceendings of the IEEE Wireless Communications and Networking (WCNC 2003), New Orleans, LA, USA, March 2003.Google Scholar
  5. 5.
    S. Upadhyayula, V. Annamalai, S.K.S. Gupta, “A low-latency and energy-efficient algorithm for convergecast in wireless sensor networks”, in Proceedings of IEEE Global Telecommunications Conference (GLOBECOM '03), San Francisco, CA, USA, January 2003.Google Scholar
  6. 6.
    S.S. Kulkarni and M.(U.) Arumugam, “SS-TDMA: A Self-Stabilizing MAC for Sensor Networks”, Sensor Network Operations, IEEE Press, 2005.Google Scholar
  7. 7.
    M.S. Pan, Y.-C. Tseng, “Quick convergecast in ZigBee beacon-enabled tree-based wireless sensor networks”, Computer Communications, Vol. 31, Issue 5, pp. 999-1011, Elsevier, 25 March 2008.CrossRefGoogle Scholar
  8. 8.
    K. L. Bryan, T. Ren, L. DiPippo, T. Henry, V. Fay-Wolfe, “Towards Optimal TDMA Frame Size in Wireless Sensor Networks”, University of Rhode Island, Technical Report, TR-xxx, March 2007.Google Scholar
  9. 9.
    G. Lu, B. Krishnamachari, “Minimum latency joint scheduling and routing in wireless sensor networks”, Ad Hoc Networks, Vol. 5, Issue 6, pp. 832-843, Elsevier, August 2007.CrossRefGoogle Scholar
  10. 10.
    J. Mao, Z. Wu, X. Wu, “A TDMA scheduling scheme for many-to-one communications in wireless sensor networks”, Computer Communications, Vol. 30, Issue 4, pp. 863-872, Elsevier, February 2007.CrossRefGoogle Scholar
  11. 11.
    J. Polastre, J. Hill, D. Culler, “Versatile Low Power Media Access for Wireless Sensor Networks”, in Proceedings of the 2nd ACM SenSys Conference, pp. 95-107, Baltimore, MD, USA, November. 2004.Google Scholar
  12. 12.
    T. Rappaport, “Wireless Communications: Principles and Practice”, 2nd Edition, Prentice Hall, 2002.Google Scholar
  13. 13.
    T. H. Cormen, C. E. Leiserson, R. L. Rivest, “Introduction to Algorithms”, The MIT Press, 2000.Google Scholar

Copyright information

© International Federation for Information Processing 2008

Authors and Affiliations

  • Mário Macedo
    • 1
  • Mário Nunes
    • 1
    • 3
  • António Grilo
    • 1
    • 2
  1. 1.INESC-ID, Rua Alves RedolLisboaPortugal
  2. 2.IST/UTL, Av. Rovisco PaisLisboaPortugal
  3. 3.FCT/UNLCaparicaPortugal

Personalised recommendations