The performance of wavelength division multiplexing (WDM) networks is highly dependent on the wavelength converter allocation and routing problems. Typically, these problems have been treated as independent problems under dynamic traffic; however, in order to achieved good system's performance, both problems should be dealt with together. To this aim, this work proposes a joint optimization approach where allocations for converters and paths for routing are calculated simultaneously. A multi-objective evolutionary algorithm is proposed to minimize the number of wavelength converters and the overall blocking probability at the same time. Extensive simulations show promising results in the sense that our approach not only generates better trade-off solutions in comparison with an iterative-joint state-of-the-art approach but also constitutes an effective tool to better understand different trade-offs in the design of WDM networks.

Routing and wavelength converter allocation in WDM networks: a multi-objective evolutionary optimization approach

Wavelength converters are effective to reduce connection blocking probability in dynamic WDM networks. Full complete conversion, where all the output wavelengths of each node are equipped with converters, provides the best performance. However, it requires huge amount of wavelength converters, which are expected to be quite expensive in the foreseeable future. On the other hand, partial conversion leads to much less cost by reducing the number of converters in each node. To approximate the best performance provided by full complete conversion using partial conversion, two questions have to be answered: a) How many converters does the network need? b) What are the optimal converter locations? For the first time, this paper presents the answers using a heuristic algorithm based on an analytical model. In particular, we develop an algorithm to deal with the case in real networks where the accurate traffic estimation is not available. Our approach is shown to be both efficient and effective: the calculation in either NSFNet or EON needs no more than 30 seconds using an ordinary PC; and the designed networks with partial conversion ability approximate the best performance very well under both uniform and non-uniform traffic.

How many wavelength converters do we need

In this paper, we study the converter placement problem with static traffic in wavelength division multiplexing ring networks using sparse wavelength conversion. Three heuristic techniques, genetic algorithms (GA), simulated annealing (SA) and tabu search (TS), are utilized to solve this combinatorial optimization problem. Also, an alternative method, integer programming based heuristic (Lagrangian heuristic), is utilized to compare with the results of the three heuristic techniques. In order to investigate how effective the wavelength conversion is, we employ three approaches: (i) without wavelength conversion (i.e. no converter is allowed to be placed in the network); (ii) with wavelength conversion and each of the nodes has a converter placed, to compare with the approach of the converter placement problem; and (iii) with wavelength conversion and some nodes have a converter placed. We have considered three different scenarios in the simulation: (a) 10-node network; (b) 15-node network; and (c) 20-node network. The simulation results show that GA is able to find better solutions than SA, TS and Lagrangian heuristic in three different scenarios. Also, it is found that placing some wavelength converters in the network can minimize the total number of used wavelengths effectively and placing converters on only some nodes can reach the same performance as that when placing converters on all nodes.

Solving the Converter Placement Problem in WDM Ring Networks using Genetic Algorithms

Equipping all nodes of a large optical network with full conversion capability is prohibitively costly. To improve performance at reduced cost, sparse converter placement algorithms are used to select a subset of nodes for full-conversion deployment. Further cost reduction can be obtained by deploying only limited conversion capability in the selected nodes. We present a limited wavelength converter placement algorithm based on the k-minimum dominating set (k-MDS) concept. We propose three different cost-effective optical switch designs using the technologically feasible nontunable optical multiplexers. These three switch designs are flexible node sharing, strict node sharing, and static mapping. Compared to the full search heuristic of O(N 3 ) complexity based on ranking nodes by blocking percentages, our algorithm not only has a better time complexity O(RN 2 ), where R is the number of disjoint sets provided by k-MDS, but also avoids the local minimum problem. The performance benefit of our algorithm is demonstrated by network simulation with the U.S Long Haul topology having 28 nodes (R is 5) and the National Science Foundation (NSF) network having 16 nodes (R is 4). Our simulation considers the case when the traffic is not uniformly distributed between node pairs in the network using a weighted placement approach, referred to as k-WMDS. From the optical network management point of view, our results also show that the limited conversion capability can achieve performance very close to that of the full conversion capability, while not only decreasing the optical switch cost but also enhancing its fault tolerance.

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Architecture and sparse placement of limited-wavelength converters for optical networks

Multi-objective routing and wavelength converter allocation under uncertain traffic

We consider WDM networks with lightpath switching where wavelengths may be converted, as required, along the lightpath. For efficient converter usage in such a network, sparse converter placement may be followed where only some of the network nodes are equipped with wavelength converters. Given the nominal network traffic pattern, we present a simple heuristic algorithm which may be used to determine the location of these converters for good network performance. For a network designed in this fashion, we consider the application of a path-metric based heuristic algorithm for lightpath routing and wavelength selection along the links of the selected route. Dynamic operation of the sparse converter network is considered using this path-metric based algorithm for lightpath routing and wavelength selection.

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B. Popat

Papers

Sparse converter placement in WDM networks and their dynamic operation using path-metric based algorithms