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

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

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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.

Inspec keywords: stochastic automata; telecommunication network routing; multicast communication; trees (mathematics); learning automata

Other keywords: dynamic membership environment; algorithm; minimum cost delay bounded multicast routing; distributed stochastic learning automata; tree

Subjects: Communication network design, planning and routing; Combinatorial mathematics

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