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Computer Communications
Volume 27, Issue 5, 20 March 2004, Pages 387-399
 
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doi:10.1016/j.comcom.2003.08.003    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2003 Elsevier B.V. All rights reserved.

Benefits of traffic engineering using QoS routing schemes and network controls

Shekhar Srivastava , Balaji Krithikaivasan , Cory Beard Corresponding Author Contact Information, E-mail The Corresponding Author, Deep Medhi , Appie van de Liefvoort , Wesam Alanqar and Ananth Nagarajan

Division of Computer Science and Electrical Engineering, School of Computing and Engineering, University of Missouri-Kansas City, 550G Flarsheim Hall, 5100 Rockhill Road, Kansas City, MO 64110, USA

Received 31 July 2002; 
Revised 15 July 2003; 
accepted 6 August 2003. 
Available online 4 September 2003.

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Abstract

We demonstrate the benefits of traffic engineering by studying three realistic network models derived from an actual service provider network. We evaluate traffic engineering in the presence of QoS-based routing schemes compared with Destination-Based Routing, the default routing behavior for the Internet. We also simulate prioritization of important traffic flows by implementing priority in one or more of the path caching, path ordering, and actual route selection phases of the constraint-based routing framework. We observe that traffic engineering can provide 20–50% network capacity savings. We also observe that prioritization in more than one phase of constraint-based routing can provide even more significant benefits.

Author Keywords: Author Keywords: Traffic engineering; Constraint-based routing; Quality of service routing

Article Outline

1. Introduction
2. Priority mechanisms
2.1. Priority in the PPC phase (number of cached paths)
2.2. Priority in the UPO phase (choice of routing schemes)
2.3. Priority in the ARS phase (activation of control)
2.3.1. No Control
2.3.2. Trunk reservation
2.3.3. Service Class based Trunk Reservation
2.3.4. Service Class based Multi-Link Trunk Reservation
3. Simulation environment and network setup
3.1. Network topology
3.2. Traffic models
3.3. Service classes
3.4. Traffic matrix
3.5. Performance metric
3.6. Notation
3.7. Experiment setup
4. Results and discussion
4.1. Basic results
4.2. Changing traffic matrices between 5% S1 and 20% S1
4.3. Interactions between routing schemes, Ks1, and Kosvc
4.3.1. RSs1=MACRPC and RSosvc=DRR
4.3.2. General conclusions
4.4. Changing network capacity
4.5. Overloaded networks—Networks II and III
4.5.1. Network II—proportional decrease
4.5.2. Network III—link reduction and proportional decrease
5. Conclusion
References






Computer Communications
Volume 27, Issue 5, 20 March 2004, Pages 387-399
 
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