A New Method for Solving Routing and Wavelength Assignment Problems under Inaccurate Routing Information in Optical Networks with Conversion Capability

In this paper a novel approach for modelling Routing and Wavelength Assignment (RWA) problem in wavelength-routed Dense Wavelength Division Multiplexing (DWDM) optical networks is proposed. A new idea based on Artificial Bee Colony (ABC) algorithm is introduced for solving RWA problem which is known to be an NP-hard problem. In the proposed ABC-RWA approach every food source represents a possible and feasible lightpath between each original and destination node pair in demand matrix. The positions of food sources are modified by some artificial bees in the population where the aim is to discover the places of food sources. The food source with the highest nectar value seems to be a solution which is evaluated by the fitness function. The simulation results demonstrate the ability and efficiency of proposed approach for solving RWA in real-world optical networks. The proposed approach could be extended for dynamic RWA schemes in real-time applications and employed by network resilience architectures.

In the past few decades, the architecture of optical networks has undergone significant evolution, from the earliest wavelength-division multiplexing (WDM) optical networks to elastic optical networks (EONs) and later to space-division multiplexing (SDM) EONs, to address the continuous growth of Internet traffic. By 2024, Pbps-level optical networks are expected, far exceeding the capacity limit of single-mode fibers. The massive SDM era is on the horizon. In this context, a newly designed architecture for optical networks called the spatial channel network (SCN) architecture, which achieves high cost efficiency by means of practical hierarchical optical cross-connects, has recently been proposed. However, the evolution of optical network architectures will simultaneously present challenges related to network optimization. For instance, with the evolution from WDM optical networks to EONs, the kernel network optimization problem was transformed from the routing and wavelength assignment (RWA) problem into the routing and spectrum assignment (RSA) problem due to the additionally introduced constraint of spectrum contiguity. Similarly, specially designed algorithms are also expected to be essential for addressing the network optimization problem in SCNs. In this paper, we define this new problem as the routing, spatial channel, and spectrum assignment (RSCSA) problem. We propose an integer linear programming (ILP) model and a heuristic algorithm to solve the RSCSA problem. We examine the performance of the proposed approaches via simulation experiments. The results show that both proposed approaches are effective in finding the optimal solutions or solutions close to the lower bounds. To the best of our knowledge, this is the first work to focus on the network optimization problem in SCNs.

A fundamental problem in computer and communication networks is the wavelength assignment (WA) problem: given a set of routing paths on a network, assign wavelengths (channels) to the paths such that the paths with the same wavelength are edge-disjoint. The optimization problem here is to minimize the number of wavelengths. A popular network topology is a tree of rings. It is known NP-hard to find the minimum number of wavelengths for the WA problem on a tree of rings. Let L be the maximum number of paths on any edge in the network. Then L is a lower bound on the number of wavelengths for the WA problem. We give a polynomial time algorithm which uses at most 3L wavelengths for the WA problem on a tree of rings with node degree at most eight. This improves the previous result of 4L. We also show that some instances of the WA problem require at least 3L wavelengths on a tree of rings, implying that the 3L upper bound is optimal for the worst case instances. In addition, we prove that our algorithm has approximation ratios 2 and 2.5 for a tree of rings with node degrees at most four and six, respectively.

SUMMARYThe future of designing optical networks focuses on the wavelength division multiplexing technology. This technology divides the huge bandwidth of an optical fiber into different wavelengths, providing different available channels per link of optical fiber. However, when it is required to establish a set of demands, a problem comes up. This problem is known as routing and wavelength assignment problem. In this work, we have tackled the static routing and wavelength assignment problem by using multiobjective evolutionary computing. The algorithm applied is the differential evolution but modified with the Pareto tournaments concept for being adapted to the multiobjective context. By using OpenMP, an application programming interface that supports multiplatform shared memory multiprocessing programming, we have demonstrated that this algorithm is highly suitable to be parallelized. We have performed several experiments in multicore systems with two, four, and eight cores, obtaining 97.57% of mean efficiency. To ensure that our heuristic obtains relevant results, we have compared it with a parallel version of the standard fast nondominated sorting genetic algorithm. Finally, in order to show the goodness and effectiveness of the differential evolution with Pareto tournaments algorithm when dealing with this problem, we present diverse multiobjective comparisons with the nondominated sorting genetic algorithm and other approaches published in the literature. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper we consider the routing and wavelength assignment problem in a wavelength routed all optical network. Inspired by techniques from artificial intelligence, in particular the Blocking Island (BI) abstraction, we propose a simple and intelligent routing and wavelength assignment (RWA) algorithm: BI_RWA. This algorithm can be used in arbitrarily connected optical networks. In addition, it is general enough such that with some simple modifications, it can be applied to different optical networking scenarios: static or dynamic traffic, single or multiple fiber links between node pairs, with or without wavelength converters. We have conducted simulation experiments to evaluate the performance of our algorithm. The simulation is carried out in two parts: static traffic and dynamic traffic. The results will demonstrate that our RWA algorithm outperforms state-of-the-art related algorithms.

In WDM networks, static Routing Wavelength Assignment (RWA) problem is NP-complete. The Integer Linear Programming (ILP) is too complicated to implement. In most existing algorithms, it is usually split into routing and wavelength assignment, which is not completely precise. Mainly motivated by that imprecision, the Layered-Graph model was introduced into static RWA problem, which can consider the routing and wavelength assignment jointly. Three proposed algorithms using this model are described in this paper. Their performances are also evaluated by series of exhaustive simulations.

A post-optimization method for the routing and wavelength assignment problem applied to scheduled lightpath demands

Multicast routing for wavelength division multiplexing optical network is a challenging problem in optical networks. The Multicast Routing and Wavelength Assignment (MRWA) problem has been proved to be a NP complete problem. In this paper, the MRWA problem in Wavelength Division Multiplexing (WDM) has been modeled as a Multi-Objective Multicast Routing and Wavelength Assignment (MOMRWA) optimization problem with three optimization objectives, including minimizing the resource cost, minimizing the end-to-end delay and minimizing the used channels. Some Quality of Service metrics have also been considered in MOMRWA. To tackle the MOMRWA problem, a multi-objective genetic algorithm, namely MRWA_SSNSGA-II, has been proposed, which is based on the Steady-State Non-Dominated Sorting Genetic Algorithm II combined with the Efficient Non-Domination Level Update (ENLU) strategy. The purpose of the ENLU strategy is to reduce the computing time of maintaining the Non-Domination Level structure. In order to avoid the loop generated by the gene recombination, a light tree recovery mechanism based on the Minimum Path Cost Heuristic has been proposed. We evaluate our proposed MRWA_SSNSGA-II on a large number of test instances with different sizes. Experimental results demonstrate that MRWA_SSNSGA-II outperformed some recent GA based multi-objective optimization algorithms for MOMRWA problem in terms of the solution quality.

We investigate the problem of online routing and wavelength assignment and the related throughput maximization problem in wavelength division multiplexing optical networks. It is pointed out that these problems are highly inapproximable, that is, the competitive ratio of any algorithm is at least a polynomial. We evaluate the average-case performance of several online algorithms, which have no knowledge of future arriving connection requests when processing the current connection request. Our experimental results on a wide range of optical networks demonstrate that the average-case performance of these algorithms are very close to optimal.

In this paper, we propose a new ant-based algorithm for the dynamic routing and wavelength assignment (RWA) problem in optical WDM networks under the wavelength continuity constraint. Unlike conventional approaches, which usually require centralized global network information, our new RWA algorithm constructs the routing solution in a distributed manner by means of cooperative ants. To facilitate the ants’ foraging task, we adopt in our algorithm a probabilistic routing table structure for route selection. The new algorithm is highly adaptive in that it always keeps a suitable number of ants in the network to cooperatively explore the network states and continuously update the routing tables, so that the route for a connection request can be determined promptly by the current states of routing tables with only a small setup delay. Some new schemes for path scoring and path searching are also proposed to enhance the performance of our ant-based algorithm. Extensive simulation results upon three typical network topologies indicate that the proposed algorithm has a very good adaptability to traffic variations and it outperforms both the fixed routing algorithm and the promising fixed–alternate routing algorithm in terms of blocking probability. The ability to guarantee both a low blocking probability and a small setup delay makes the new ant-based routing algorithm very attractive for both the optical circuit switching networks and future optical burst switching networks

A wavelength-routed optical network consists of a number of cross-connects which are interconnected by optical fibers. Transparent optical networks allow signals to bypass extensive electronic signal processing at intermediate nodes. The quality of an optical signal degrades as it travels though several optical components along its lightpath. It is essential to incorporate imapact of the physical impairments in the routing and wavelength assignment (RWA) problem in transparent optical networks. This work compiles a comprehensive survey, from various research publications, of the proposed algorithms that address this issue. The physical layer impairments classification in optical networks are initially presented followed by physical layer impairments (PLI) RWA algorithms and algorithmic approaches for the PLI-RWA problem. Performance metrics for evaluating the performance of the proposed PLI-RWA algorithms are presented at the end of the work. Further research topics are presented in this study.

In this paper we consider the wavelength requirement for all‐optical networks based on wavelength‐division multiplexing (WDM). Given a static channel demand, the problem of routing and wavelength assignment (RWA) in such networks has to be solved. Due to the restricted number of wavelengths available on each link it is desirable to get a solution of the RWA problem, in which the needed number of wavelengths is minimized. Unfortunately, this optimization problem belongs to the class of NP‐complete problems. Therefore in this paper we present a new powerful method for the approximative solution of the RWA problem. This new approach is based on the combination of a genetic algorithm and a quite simple heuristic. The efficiency of this combined algorithm is demonstrated by the application to some well known benchmark problems.

In wavelength division multiplexed all optical networks; lightpath establishes a connection between sending and receiving nodes bypassing the electronic processing at intermediate nodes. One of the prime objectives of Routing and Wavelength Assignment (RWA) problem is to maximize the number of connections efficiently by choosing the best routes. Although there are several algorithms available, improving the blocking performance in optical networks and finding optimal solutions for RWA problem has still remained a challenging issue. Wavelength conversion can be helpful in restricting the problem of wavelength continuity constraint but it increases complexity in the network. In this paper, we propose new weight dependent routing and wavelength assignment strategy for all optical networks without use of wavelength converters. Proposed weight function reduces blocking probability significantly, improving the network performance at various load conditions. Further, due to absence of wavelength converters, the cost and complexity of network reduces. Results show that the proposed strategy performs better than earlier reported methods.

Statistical multiplexing at the optical layer has been considered a critical requirement in order to build the next generation of ultra-high capacity optical transport networks in a cost-efficient manner. However, even today, the state of the art of commercially available optical core networks is based on mature wavelength switching and routing technologies, which lack a transport and control plane architecture that can support statistical traffic multiplexing with guaranteed Quality of Service (QoS) across a wide range of QoS parameters even if they can support fast reconfiguration at msec time scales. For several years, most research efforts have focused on the concepts of Optical Burst Switching (OBS) and Optical Packet Switching (OPS), which are based on the hybrid use of electronic nodes and optical switches to exploit Time Division Multiplexing (TDM) in order to achieve statistical multiplexing and dynamic resource reservation over optical networks. While burst switching has been experimentally proven as a technically feasible technique, its performance suffers especially under strict requirements for QoS guarantees. In this paper we evaluate the performance gains that can be achieved exploiting statistical multiplexing over a large scale core optical network and we demonstrate the efficiency of the CANON architecture (Clustered Architecture for Nodes in an Optical Network) as a viable alternative to OBS, which can achieve both targets for statistical multiplexing gains and QoS guarantees at the same time.

The Static RWA (Routing and Wavelength Assignment) problem in Optical Networks is a combinatorial optimization problem fit to iterative search methods. In this article we further investigate the static manycast RWA problem in optical networks and solve it using an evolutionary programming (EP) strategy such that the number of the manycast requests established for a given number of wavelengths is maximized. The proposed algorithm solves, approximately, the wavelength assignment problem while a backtracking approach is used to solve the routing issue. We present the details of our proposed algorithm and compare it to another metaheuristic named genetic algorithm (GA). EP shows a 24 % improvement over GA.