SRLG-diverse routing of multiple circuits in a heterogeneous optical transport network

Dahai Xu, Guangzhi Li, Byrav Ramamurthy, Angela Chiu, Dongmei Wang, Robert Doverspike
October 2011
Cite DOI URL

Abstract

Network planners are often requested to provision multiple physically-diverse high-speed circuits over a large carrier’s core (inter-city) DWDM network, which consists of multiple layers and heterogeneous vendor systems. Optimally provisioning such circuits while avoiding shared risk link group (SRLG) failures is an NP-hard problem. In this paper, we propose a novel hybrid two-step approach: pre-processing with Integer Linear Programming (ILP) for diverse routing and postprocessing for regenerator placement and wavelength assignment. This approach has been implemented in a prototype network planning tool. According to our experiments, most of the cases for a typical large carrier’s core transport network can be solved within 1 minute, even with tens of thousands of binary decision variables, which allows interactive use by network planners.

Type
Conference paper
Publication
2011 8th International Workshop on the Design of Reliable Communication Networks (DRCN)
Optical Fiber Networks Repeaters Telecommunication Network Routing Wavelength Division Multiplexing Wavelength Assignment Integer Programming Linear Programming Routing Diverse Routing Shared Risk Link Group Integer Linear Programming Telecommunication Network Planning ILP Heterogeneous Optical Network SRLG Regenerator Placement Binary Decision Diagrams Binary Decision Variable DWDM Network Fiber Optics Heterogeneous Optical Transport Network Heterogeneous Vendor System Hybrid Two-Step Approach Multiple Circuit Multiple Physically-Diverse High-Speed Circuit Network Planner NP-Hard Problem Prototype Network Planning Tool SRLG-Diverse Routing
Byrav Ramamurthy
Byrav Ramamurthy
Professor & PI

My research areas include optical and wireless networks, peer-to-peer networks for multimedia streaming, network security and telecommunications. My research work is supported by the U.S. National Science Foundation, U.S. Department of Energy, U.S. Department of Agriculture, NASA, AT&T Corporation, Agilent Tech., Ciena, HP and OPNET Inc.