Name
Title | ||
|---|---|---|
Cost efficient traffic grooming and regenerator placement in impairment-aware optical WDM networks |
Abstract | ||
|---|---|---|
In this paper, we address the problem of traffic grooming and regenerator placement in a WDM optical network in which lightpaths are hop-constrained by physical impairments. The efficient placement of regenerators and electronic grooming equipment at ROADM nodes for a given network topology is required such that all traffic demands can be supported with minimum cost. We present a detailed ROADM node architecture together with an associated cost model. We model the problem by Integer Linear Programming (ILPs) and propose an auxiliary-graph-based heuristic for jointly placing regenerators and electronic grooming equipment in the network. To evaluate the performance of the proposed heuristic, we also derive a lower bound on the network cost. The numerical results show that combining the grooming problem with the placement of regenerators reduces the network cost significantly compared to the cases in which traffic grooming and regenerator placement are handled separately. The performance of the proposed polynomial-time heuristic is very close to the lower bound and approaches the bound as the network load increases. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.osn.2011.03.010 | Optical Switching and Networking |
Keywords | Field | DocType |
Traffic grooming,Regenerator,Impairment-aware network,Optical WDM network,ROADM | Wavelength-division multiplexing,Heuristic,Upper and lower bounds,Computer science,Computer network,Network topology,Integer programming,Regenerative heat exchanger,Cost efficiency,Traffic grooming,Distributed computing | Journal |
Volume | Issue | ISSN |
9 | 3 | 1573-4277 |
Citations | PageRank | References |
2 | 0.50 | 6 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ankitkumar N. Patel | 1 | 62 | 7.14 |
| Chengyi Gao | 2 | 11 | 2.84 |
| Jason P. Jue | 3 | 533 | 59.51 |
| Xi Wang | 4 | 61 | 20.91 |
| Qiong Zhang | 5 | 151 | 35.79 |
| Paparao Palacharla | 6 | 52 | 19.22 |
| Takao Naito | 7 | 10 | 3.25 |