ICALP 2010: Automata, Languages and Programming pp 333-344

# Placing Regenerators in Optical Networks to Satisfy Multiple Sets of Requests

• George B. Mertzios
• Ignasi Sau
• Mordechai Shalom
• Shmuel Zaks
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6199)

## Abstract

The placement of regenerators in optical networks has become an active area of research during the last years. Given a set of lightpaths in a network G and a positive integer d, regenerators must be placed in such a way that in any lightpath there are no more than d hops without meeting a regenerator. While most of the research has focused on heuristics and simulations, the first theoretical study of the problem has been recently provided in [10], where the considered cost function is the number of locations in the network hosting regenerators. Nevertheless, in many situations a more accurate estimation of the real cost of the network is given by the total number of regenerators placed at the nodes, and this is the cost function we consider. Furthermore, in our model we assume that we are given a finite set of p possible traffic patterns (each given by a set of lightpaths), and our objective is to place the minimum number of regenerators at the nodes so that each of the traffic patterns is satisfied. While this problem can be easily solved when d = 1 or p = 1, we prove that for any fixed d,p ≥ 2 it does not admit a $$\textsc{PTAS}$$, even if G has maximum degree at most 3 and the lightpaths have length $$\mathcal{O}(d)$$. We complement this hardness result with a constant-factor approximation algorithm with ratio ln (d ·p). We then study the case where G is a path, proving that the problem is NP-hard for any d,p ≥ 2, even if there are two edges of the path such that any lightpath uses at least one of them. Interestingly, we show that the problem is polynomial-time solvable in paths when all the lightpaths share the first edge of the path, as well as when the number of lightpaths sharing an edge is bounded. Finally, we generalize our model in two natural directions, which allows us to capture the model of [10] as a particular case, and we settle some questions that were left open in [10].

## Keywords

optical networks regenerators overprovisioning approximation algorithms hardness of approximation

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## Authors and Affiliations

• George B. Mertzios
• 1
• Ignasi Sau
• 2
• Mordechai Shalom
• 3
• Shmuel Zaks
• 2
1. 1.Department of Computer ScienceRWTH Aachen UniversityAachenGermany
2. 2.Department of Computer ScienceTechnionHaifaIsrael
3. 3.TelHai Academic College, Upper GalileeIsrael