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Computer Networks
Volume 50, Issue 12, 24 August 2006, Pages 2054-2070
Network Modelling and Simulation
 
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doi:10.1016/j.comnet.2005.09.027    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2005 Elsevier B.V. All rights reserved.

A framework for realistic and systematic multicast performance evaluationstar, open

Li Laoa, Corresponding Author Contact Information, E-mail The Corresponding Author, Jun-Hong Cuib, E-mail The Corresponding Author and Mario Gerlaa, E-mail The Corresponding Author

aComputer Science Department, University of California, Los Angeles, CA 90095-1596, United States bComputer Science and Engineering Department, University of Connecticut, Storrs, CT 06269-2155, United States

Available online 7 November 2005.

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Abstract

Previous multicast research often makes commonly accepted but unverified assumptions on network topologies and group member distribution in simulation studies. In this paper, we propose a framework to systematically evaluate multicast performance for different protocols. We identify a series of metrics, and carry out extensive simulation studies on these metrics with different topological models and group member distributions for three case studies. Our simulation results indicate that realistic topology and group membership models are crucial to accurate multicast performance evaluation. These results can provide guidance for multicast researchers to perform realistic simulations, and facilitate the design and development of multicast protocols.

Keywords: Multicast; Performance evaluation; Topology models; Group membership models; Power-law

Article Outline

1. Introduction
2. Related work
2.1. Topology generators
2.2. Group member models
2.3. Multicast performance evaluation
3. The systematic and realistic performance evaluation framework
3.1. Models and parameters
3.1.1. Topology models and parameters
3.1.2. Membership model and parameters
3.2. Case studies
3.2.1. SBT vs. CBT
3.2.2. Multicast state scalability
3.2.3. Application-layer multicast: Narada vs. NICE
3.3. Metrics of interest
3.3.1. Routing performance
3.3.2. Multicast efficiency
3.3.3. State scalability
3.3.4. Link stress
3.3.5. Control overhead
4. Simulation results
4.1. Simulation setup
4.2. Multicast routing algorithms
4.2.1. AS-level topologies
4.2.1.1. Delay ratio
4.2.1.2. Cost ratio
4.2.1.3. Efficiency
4.2.2. Router-level topologies
4.2.2.1. Delay ratio
4.2.2.2. Efficiency
4.2.3. Group membership distributions
4.3. Multicast state scalability
4.3.1. Intra-group state aggregation
4.3.2. Inter-group state aggregation
4.4. Application-layer multicast
4.4.1. AS-level topologies
4.4.1.1. Delay ratio
4.4.1.2. Link stress ratio
4.4.1.3. Cost ratio and control overhead ratio
4.4.2. Router-level topologies
4.5. Lessons learned
5. Conclusion
5.1. Future work
References
Vitae





















Computer Networks
Volume 50, Issue 12, 24 August 2006, Pages 2054-2070
Network Modelling and Simulation
 
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