Historical data learning based dynamic LSP routing for overlay IP over WDM networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In overlay IP over WDM networks, there are only limited information exchanges between the two layers through the user network interface (UNI) [1] for service requests and responses. To enhance the overlay network performance while maintaining its simplicity, we propose for the first time to learn from the historical data of lightpath setting up costs maintained by the logical layer network operator(s), to facilitate the logical layer routing process. Using a simple cost updating strategy to alleviate the logical layer cost outdating issue, we present two dynamic LSP routing algorithms, namely Existing Link First (ELF) and Enquiries-First (ENF), for the overlay network architecture. Simulation results show that the proposed algorithms achieve much better performance than the existing algorithms with or without constraint on the number of optical ports.

Original languageEnglish
Title of host publicationICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing
DOIs
StatePublished - 2009
Externally publishedYes
Event7th International Conference on Information, Communications and Signal Processing, ICICS 2009 - Macau Fisherman's Wharf, Macao
Duration: 8 Dec 200910 Dec 2009

Publication series

NameICICS 2009 - Conference Proceedings of the 7th International Conference on Information, Communications and Signal Processing

Conference

Conference7th International Conference on Information, Communications and Signal Processing, ICICS 2009
Country/TerritoryMacao
CityMacau Fisherman's Wharf
Period8/12/0910/12/09

Keywords

  • Historical data learning
  • IP over WDM
  • Optical networks
  • Overlay model
  • Routing algorithms

Fingerprint

Dive into the research topics of 'Historical data learning based dynamic LSP routing for overlay IP over WDM networks'. Together they form a unique fingerprint.

Cite this