Research Article
Approximating Optimal Survivable Scheduled Service Provisioning in WDM Optical Networks with Iterative Survivable Routing
@INPROCEEDINGS{10.1109/BROADNETS.2006.4374348, author={Tianjian Li and Bin Wang}, title={Approximating Optimal Survivable Scheduled Service Provisioning in WDM Optical Networks with Iterative Survivable Routing}, 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.2006.4374348} }
- Tianjian Li
Bin Wang
Year: 2006
Approximating Optimal Survivable Scheduled Service Provisioning in WDM Optical Networks with Iterative Survivable Routing
BROADNETS
IEEE
DOI: 10.1109/BROADNETS.2006.4374348
Abstract
Survivable service provisioning design has emerged as one of the most important issues in communication networks in recent years. In this work, we study survivable service provisioning with shared protection under a scheduled traffic model in wavelength convertible WDM optical mesh networks. In this model, a set of demands is given, and the setup time and teardown time of a demand are known in advance. Based on different protection schemes used, this problem has been formulated as integer linear programs with different optimization objectives and constraints in our previous work [8, 9]. The problem is shown to be NP- hard. We therefore study time efficient approaches to approximating the optimal solution to the problem. Our proposed approach is based on an iterative survivable routing (ISR) scheme that utilizes a capacity provision matrix and processes demands sequentially using different demand scheduling policies. The objective is to minimize the total network resources (e.g., number of wavelength-links) used by working paths and protection paths of a given set of demands while 100% restorability is guaranteed against any single failure. The proposed algorithm is evaluated against solutions obtained by integer linear programming. Our simulation results indicate that the proposed ISR algorithm is extremely time efficient while achieving excellent performance in terms of total network resources used. The impact of demand scheduling policies on the ISR algorithm is also studied.