Probing and Tree Search Techniques

  • Jeremiah F. Hayes
Part of the Applications of Communications Theory book series (ACTH)


In the two preceding chapters we have studied two contrasting techniques for sharing a common channel among a number of geographically dispersed stations. As we have seen, the two have complementary characteristics. Due to large overhead, polling is inefficient at light loading, but as loading increases the effect of overhead diminishes. In contrast, random access techniques have minimal overhead and, as a consequence, are best at light loading. However, for the random access techniques we considered the instability appears as the loading increases. A direct comparison between polling in the form of token passing and CSMA (see Figure 8.17) shows that the advantage that CSMA holds at light loading dissipates as the load increases.


Tree Search Random Access Light Loading State Transition Matrix Single Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    N. Abramson, Information Theory and Coding, McGraw-Hill, New York (1963).Google Scholar
  2. 2.
    R. G. Gallager, Information Theory and Reliable Communications, John Wiley, New York (1968).Google Scholar
  3. 3.
    J. F. Hayes, “An Adaptive Technique for Local Distribution,” IEEE Transactions on Communications, COM-26(8), 1178–1186, August (1978).CrossRefGoogle Scholar
  4. 4.
    M. Sobel and P. A. Groll, “Group Testing to Eliminate Efficiently All Defectives in a Binomial Sample,” Bell System Technical Journal, 38, 1179–1253, September (1959).MathSciNetGoogle Scholar
  5. 5.
    R. Dorfman, “Detection of Defective Members of Large Populations,” Annals of Mathematical Statistics, 28, 1033–1036 (1953).Google Scholar
  6. 6.
    T. Berger, N. Mehravari, D. Towsley, and J. K. Wolf, “Random Multiple Access Communication and Group Testing,” IEEE Transactions on Communications, Com-32(7), July (1984).Google Scholar
  7. 7.
    J. Capetanakis, “Tree Algorithms for Packet Broadcast Channels,” IEEE Transactions on Information Theory, IT-25, 505–515, September (1979).MathSciNetCrossRefGoogle Scholar
  8. 8.
    B. Tsybakov and V. A. Mikhailov, “Free Synchronous Packet Access in a Broadcast Channel with Feedback,” Problems of Information Transmission, 14, 259–280, April (1979).Google Scholar
  9. 9.
    A. Grami, J. F. Hayes, and K. Sohraby, “Further Results on Probing,” Proceedings of the International Conference on Communications, Philadelphia, 1982. pp. IC3.1–IC.3.5 (1982).Google Scholar
  10. 10.
    J. L. Massey, “Collision Resolution Algorithms and Random-Access Communications,” Technical report, UCLA-ENG-8016, April (1980).Google Scholar
  11. 11.
    R. C. Gallager, “Conflict Resolution in Random Access Broadcast Networks,” Proceedings of the AFSOR Workshop in Communication Theory and Applications, September 17–20, Provincetown, Massachusetts (1978), pp. 74–76.Google Scholar
  12. 12.
    J. Mosley, “An Efficient Contention Resoution Algorithm for Multiple Access Channels,” Report LIDS-TH-918, Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, June (1979).Google Scholar
  13. 13.
    T. Berger, N. Mehravari, and G. Munson, “On Genie-Aided Upper Bounds to Multiple Access Contention Resolution Efficiency,” Proceedings of the 1981 Annual Conference on Information Sciences and Systems, The Johns Hopkins University, Baltimore, Maryland.Google Scholar
  14. 14.
    J. I. Capetanakis, “Generalized TDMA: The Multi-Accessing Tree Protocol,” IEEE Transactions on Communications, COM-27, 1476–1484, October (1979).CrossRefGoogle Scholar
  15. 15.
    M. L. Molle, “On the Capacity of Infinite Population Multiple Access Protocols,” Computer Science Department, UCLA (1980).Google Scholar
  16. 16.
    N. Pippenger, “Bounds on the Performance of Protocols for a Multiple Access Broadcast Channel,” IEEE Transactions on Information Theory, IT-27(2), 145–152, March (1981).MathSciNetCrossRefGoogle Scholar
  17. 17.
    Y. Yemini and L. Kleinrock, “An Optimal Adaptive Scheme for Multiple Access Broadcast Communications,” Proceedings, 1978 International Communications Conference, pp. 7.2.1–7.2.5.Google Scholar
  18. 18.
    B. Tsybakov and V. A. Mikhailov, “Free Synchronous Packet Access in a Broadcast Channel with Feedback,” Problems of Information Transmission, 14, 259–280, April (1979).Google Scholar
  19. 19.
    L. Georgiadis and T. Papantoni-Kazakos, “A Collision Resolution Protocol for Random Access Channels with Energy Detectors,” IEEE Transactions on Communications, COM-30(11), 2413–2420, November (1982).CrossRefGoogle Scholar
  20. 20.
    B. S. Tsybakov, “Resolution of a Conflict of Known Multiplicity,” Problems of Information Transmission, 16(2), 134–144 [Translated from Problemy Peredachi Informatsii, 16(2), 69–82, April-June (1980)].MathSciNetMATHGoogle Scholar

Copyright information

© Plenum Press, New York 1984

Authors and Affiliations

  • Jeremiah F. Hayes
    • 1
  1. 1.Concordia UniversityMontrealCanada

Personalised recommendations