Learning algorithms for minimum cost, delay bounded multicast routing in dynamic environments

Learning algorithms for minimum cost, delay bounded multicast routing in dynamic environments

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Distributed stochastic learning automata (SLA) are used to ‘grow’ minimum cost delay bounded multicast trees in a dynamic membership environment. It is found that learning automata, which use minimal state information and require only local connectivity knowledge, provide reduced costs over shortest path approaches and comparable static costs to alternative algorithms, by learning to minimise the number of hops taken to join the tree, thereby minimising its resource consumption.


    1. 1)
      • P. Winter . Steiner problem in networks : a survey. IEEE Netw. , 2 , 129 - 167
    2. 2)
      • H.F. Salama , D.S. Reeves , Y. Viniotis . Evaluation of multicast routingalgorithms for real-time communication on high-speed networks. IEEE J. Sel. Areas Commun. , 3 , 332 - 345
    3. 3)
      • J. Reeve , P. Mars , T. Hodgkinson . Learning algorithms for quality of servicemulticast routing. Electron. Lett. , 12 , 1195 - 1197
    4. 4)
      • K.A. Narendra , M.A.L. Thathachar . (1989) Learning automata - An introduction.
    5. 5)
      • L. Kou , G. Markowsky , L. Berman . A fast algorithm for Steiner trees. Acta Informatica , 141 - 145

Related content

This is a required field
Please enter a valid email address