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2001
Subhash Suri; Marcel Waldvogel; Priyank Ramesh Warkhede
Profile-Based Routing: A New Framework for MPLS Traffic Engineering Proceedings Article
In: Boavida, Fernando (Ed.): Quality of future Internet Services, pp. 138-157, Springer Verlag, Berlin, 2001.
Abstract | BibTeX | Tags: MPLS, Quality of Service, Traffic Engineering | Links:
@inproceedings{Suri2001Profile-Based,
title = {Profile-Based Routing: A New Framework for MPLS Traffic Engineering},
author = {Subhash Suri and Marcel Waldvogel and Priyank Ramesh Warkhede},
editor = {Fernando Boavida},
url = {https://netfuture.ch/wp-content/uploads/2001/suri01profilebased.pdf},
year = {2001},
date = {2001-09-01},
urldate = {1000-01-01},
booktitle = {Quality of future Internet Services},
number = {2156},
pages = {138-157},
publisher = {Springer Verlag},
address = {Berlin},
series = {Lecture Notes in Computer Science},
abstract = { We present a new algorithm and framework for dynamic routing of bandwidth guaranteed flows. The problem is motivated by the need to dynamically set up bandwidth guaranteed paths in carrier and ISP networks. Traditional routing algorithms such as minimum hop routing or widest path routing do not take advantage of any knowledge about the traffic distribution or ingress-egress pairs, and therefore can often lead to severe network underutilization. Our work is inspired by the recently proposed ``minimum interference routing'' algorithm (MIRA) of Kodialam and Lakshman, but it improves on their approach in several ways. Our main idea is to use a ``traffic profile'' of the network, obtained by measurements or service level agreements (SLAs), as a rough predictor of the future traffic distribution. We use this profile to solve a multicommodity network flow problem, whose output is used both to guide our online path selection algorithm as well as impose admission control. The offline multicommodity solution seems very effective at distributing the routes and avoiding bottlenecks around hot spots. In particular, our algorithm can anticipate a flow's blocking effect on groups of ingress-egress pairs, while MIRA only considers one ingress-egress pair at a time. Our simulation results show that the new algorithm outperforms shortest path, widest path, and minimum interference routing algorithms on several metrics, including the fraction of requests routed and the fraction of requested bandwidth routed. Finally, the framework is quite general and can be extended in numerous ways to accommodate a variety of traffic management priorities in the network. },
keywords = {MPLS, Quality of Service, Traffic Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a new algorithm and framework for dynamic routing of bandwidth guaranteed flows. The problem is motivated by the need to dynamically set up bandwidth guaranteed paths in carrier and ISP networks. Traditional routing algorithms such as minimum hop routing or widest path routing do not take advantage of any knowledge about the traffic distribution or ingress-egress pairs, and therefore can often lead to severe network underutilization. Our work is inspired by the recently proposed “minimum interference routing” algorithm (MIRA) of Kodialam and Lakshman, but it improves on their approach in several ways. Our main idea is to use a “traffic profile” of the network, obtained by measurements or service level agreements (SLAs), as a rough predictor of the future traffic distribution. We use this profile to solve a multicommodity network flow problem, whose output is used both to guide our online path selection algorithm as well as impose admission control. The offline multicommodity solution seems very effective at distributing the routes and avoiding bottlenecks around hot spots. In particular, our algorithm can anticipate a flow’s blocking effect on groups of ingress-egress pairs, while MIRA only considers one ingress-egress pair at a time. Our simulation results show that the new algorithm outperforms shortest path, widest path, and minimum interference routing algorithms on several metrics, including the fraction of requests routed and the fraction of requested bandwidth routed. Finally, the framework is quite general and can be extended in numerous ways to accommodate a variety of traffic management priorities in the network.
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