Optimized TQ-MAP: An Adaptive Mapping Mechanism to Guarantee the Coherence of QoS Support from IP to OBS

Optimized TQ-MAP: An Adaptive Mapping Mechanism to Guarantee the Coherence of QoS Support from IP... Because of its scalability, the idea of coarse packet classification can be utilized to OBS networks. However, due to the limited number of priorities supported by OBS networks, we usually adopt a many-to-one composite class burst (CCB) assembly technique, e.g., N:1-CCB. In this kind of technique, there are two aspects related to scalable QoS support, i.e., mapping relationship and assembly resource allocation. This paper simultaneously takes the two aspects into consideration, and proposes a novel assembly mapping mechanism, called Optimized TQ-MAP, in which the most important feature is adaptivity. Based on nonlinear programming and differential calculus, it allocates the burst assembling capacity between classes fairly, efficiently and differentially, and matches IP QoS requirement with OBS QoS capacity as possible as it can. The simulation results show that Optimized TQ-MAP is more adaptive, and can efficiently guarantee the coherence of QoS support from IP to OBS. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Photonic Network Communications Springer Journals

Optimized TQ-MAP: An Adaptive Mapping Mechanism to Guarantee the Coherence of QoS Support from IP to OBS

Loading next page...
 
/lp/springer_journal/optimized-tq-map-an-adaptive-mapping-mechanism-to-guarantee-the-OV322C2J8j
Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
ISSN
1387-974X
eISSN
1572-8188
D.O.I.
10.1023/A:1025631521874
Publisher site
See Article on Publisher Site

Abstract

Because of its scalability, the idea of coarse packet classification can be utilized to OBS networks. However, due to the limited number of priorities supported by OBS networks, we usually adopt a many-to-one composite class burst (CCB) assembly technique, e.g., N:1-CCB. In this kind of technique, there are two aspects related to scalable QoS support, i.e., mapping relationship and assembly resource allocation. This paper simultaneously takes the two aspects into consideration, and proposes a novel assembly mapping mechanism, called Optimized TQ-MAP, in which the most important feature is adaptivity. Based on nonlinear programming and differential calculus, it allocates the burst assembling capacity between classes fairly, efficiently and differentially, and matches IP QoS requirement with OBS QoS capacity as possible as it can. The simulation results show that Optimized TQ-MAP is more adaptive, and can efficiently guarantee the coherence of QoS support from IP to OBS.

Journal

Photonic Network CommunicationsSpringer Journals

Published: Oct 7, 2004

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off