75
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

Performance evaluation of heuristic algorithms for routing and wavelength assignment in WDM optical networks

Pages 273-292 | Received 13 Dec 2008, Accepted 11 Feb 2009, Published online: 09 Jul 2010
 

Abstract

We evaluate the average-case performance of eight offline heuristic algorithms to solve the routing and wavelength assignment (RWA) problem and the related throughput maximisation (TM) problem in wavelength division multiplexing optical networks. These algorithms are first-fit-decreasing (FFD), first-fit-increasing (FFI), best-fit-decreasing (BFD), best-fit-increasing (BFI), densest-fit-decreasing (DFD), densest-fit-increasing (DFI), random-fit-decreasing (RFD) and random-fit-increasing (RFI). Our experimental performance evaluation is conducted by extensive simulations on a wide range of WDM optical networks, including a mesh network, four real networks and three types of random networks. We find offline RWA algorithms and TM algorithms which perform better than previously studied online algorithms, namely, first-fit (FF), best-fit (BF), densest-fit (DF) and random-fit (RF). In particular, algorithm FFD (BFD, DFD and RFD, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for RWA, and algorithm FFI (BFI, DFI and RFI, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for TM.

Acknowledgement

Two anonymous reviewers are acknowledged for their constructive comments on improving the presentation of the paper.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 763.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.