Thursday 28th of March 2024
 

Probabilistic Multicast Trees in Different Network Topology Environments


David A. Johnston, David R. Mcintyre, Francis G. Wolff and Christos A. Papachristou

Node loss and congestion changes the performance characteristics of the multicast trees. Probabilistic Multicast Trees (PMT) makes use of performance feedback, generates a probability of usage for each multicast tree based on that feedback and then makes intelligent choices about which multicast tree to use for a given packet in the presence of node loss and congestion. The advantage gained by using PMT is that it improves upon the management of the dynamic behavior of the clients where the target connectivity is constantly changing because of its feedback mechanisms and probabilistic tree selection. PMT is inserted onto three network latency topology models in a multiple tree multicast tree environment with positive improvements in the performance of data distribution.

Keywords: Network congestion, Node loss, Multicast, Application-Level Multicast, ALM, Probabilistic Multicast Trees, PMT.

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ABOUT THE AUTHORS

David A. Johnston
David A. Johnston received a Ph.D. in Engineering and Computer Science from Case Western Reserve University.

David R. Mcintyre
David R. McIntyre received a Ph.D. in Computer Science from the University of Waterloo. He is Associate Professor of Computer Science at Cleveland State University.

Francis G. Wolff
Francis G. Wolff received a Ph.D. from Case Western Reserve University. He is a Senior member of the IEEE and the Senior member of the ACM.

Christos A. Papachristou
Christos A. Papachristou is Professor of Electrical Engineering and Computer Science at Case Western Reserve. He received the Ph.D. degree in Electrical Engineering and Computer Science from Johns Hopkins University. He is a Fellow of the IEEE and a member of the ACM and Sigma XI, and is listed in Who's Who in America.


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