Research Article
Limited Grooming Architectures and Groomer-port Placement in Optical WDM Mesh Networks
@INPROCEEDINGS{10.1109/BROADNETS.2006.4374338, author={Mahesh Sivakumar and Krishna M. Sivalingam}, title={Limited Grooming Architectures and Groomer-port Placement in Optical WDM Mesh Networks}, proceedings={3rd International ICST Conference on Broadband Communications, Networks, and Systems}, publisher={IEEE}, proceedings_a={BROADNETS}, year={2006}, month={10}, keywords={}, doi={10.1109/BROADNETS.2006.4374338} }
- Mahesh Sivakumar
Krishna M. Sivalingam
Year: 2006
Limited Grooming Architectures and Groomer-port Placement in Optical WDM Mesh Networks
BROADNETS
IEEE
DOI: 10.1109/BROADNETS.2006.4374338
Abstract
In this paper, we consider the problem of traffic grooming in optical wavelength division multiplexed (WDM) mesh networks under static traffic conditions. The objective of this work is to minimize the network cost and in particular, the electronic port costs incurred for meeting a given performance goal. In earlier work, we have shown the benefits of limited grooming switch architectures, where only a subset of wavelengths in a network are equipped with expensive SONET Add Drop Multiplexers (SADM) that provide the grooming functionality. In this work, we also consider the wavelength conversion capability of such groomers. This can be achieved using a digital cross-connect (DCS) in the grooming switch to switch low-speed connections between the SADMs (and hence, between wavelengths). The grooming switch thus avoids the need for expensive optical wavelength converters. Based on these observations, we propose a limited conversion based grooming architecture for optical WDM mesh networks. The local ports at every node in this architecture can be one of three types: an add- drop port, a grooming port that allows wavelength conversion or a grooming port that does not allow wavelength conversion. The problem studied is: given a static traffic model, where should the different ports be placed in a network? We formulate this as an optimization problem using an Integer Linear Programming (ILP) and present numerical results for the same. We also present a heuristic based approach to solve the problem for larger networks.