Routing And Wavelength Assignment Problem Research Articles

Routing and wavelength assignment for folded hypercube in linear array WDM optical networks

The folded hypercube is one of the hypercube variants and is of great significance in the study of interconnection networks. In a folded hypercube, information can be broadcast using efficient distributed algorithms. In the context of parallel computing, folded hypercube has been studied as a possible network topology as an alternative to the hypercube. The routing and wavelength assignment (RWA) problem is significant, since it improves the performance of wavelength-routed all-optical networks constructed using wavelength division multiplexing approach. Given the physical network topology, the aim of the RWA problem is to establish routes for the connection requests and assign the fewest possible wavelengths in accordance with the wavelength continuity and distinct wavelength constraints. This paper discusses the RWA problem in a linear array for the folded hypercube communication pattern by using the congestion technique.

Cost minimization of multi-class demands groomed over multi-rate OTN interfaces considering WDM-layer constraints

This paper introduces a practical comprehensive approach to optimize the cost of installed Optical Transport Network (OTN) interfaces, as well as the required number of wavelengths in the substrate Wavelength Division Multiplexing (WDM) optical network. The approach assumes grooming variable-bit-rate traffic demands on multi-rate OTN interfaces. We propose an Integer Linear Programming (ILP) formulation to address the combined problem of OTN interface deployment, virtual-network formation, traffic grooming on the established distinct-capacity virtual paths, and virtual network embedding on the WDM physical substrate. The presented model focuses on mitigating the capital expenditure required to deploy OTN interfaces, usually the most costly element in the network, as well as minimizing the required number of wavelengths in the Routing and Wavelength Assignment (RWA) problem, contributing to the overall reduction in network costs and ensuring open capacity for future expansions. As the RWA problem is NP-hard and involves significant computational costs, we also propose a multi-step heuristic approach to tackle larger network instances more efficiently. In this approach, the optimization steps for the OTN design and the RWA solutions are conducted independently. For the OTN-layer planning, the optimum ILP formulation (OTN-ILP) is maintained, so that the optimum solution for the cost of installed interfaces on the OTN layer is guaranteed. The RWA problem is proposed through either an ILP formulation (RWA-ILP) or a heuristic approach. The RWA-ILP model can find the same or slightly superior number of wavelengths compared to the optimum solution of the Integrated ILP formulation, but it can provide results in reasonable times only for small networks. On the other hand, the heuristic RWA is able to run any network size, but it requires more wavelengths compared to the RWA-ILP model.

Techniques for applying reinforcement learning to routing and wavelength assignment problems in optical fiber communication networks

We propose a novel application of reinforcement learning (RL) with invalid action masking and a novel training methodology for routing and wavelength assignment (RWA) in fixed-grid optical networks and demonstrate the generalizability of the learned policy to a realistic traffic matrix unseen during training. Through the introduction of invalid action masking and a new training method, the applicability of RL to RWA in fixed-grid networks is extended from considering connection requests between nodes to servicing demands of a given bit rate, such that lightpaths can be used to service multiple demands subject to capacity constraints. We outline the additional challenges involved for this RWA problem, for which we found that standard RL had low performance compared to that of baseline heuristics, in comparison with the connection requests RWA problem considered in the literature. Thus, we propose invalid action masking and a novel training method to improve the efficacy of the RL agent. With invalid action masking, domain knowledge is embedded in the RL model to constrain the action space of the RL agent to lightpaths that can support the current request, reducing the size of the action space and thus increasing the efficacy of the agent. In the proposed training method, the RL model is trained on a simplified version of the problem and evaluated on the target RWA problem, increasing the efficacy of the agent compared with training directly on the target problem. RL with invalid action masking and this training method outperforms standard RL and three state-of-the-art heuristics, namely, k shortest path first fit, first-fit k shortest path, and k shortest path most utilized, consistently across uniform and nonuniform traffic in terms of the number of accepted transmission requests for two real-world core topologies, NSFNET and COST–239. The RWA runtime of the proposed RL model is comparable to that of these heuristic approaches, demonstrating the potential for real-world applicability. Moreover, we show that the RL agent trained on uniform traffic is able to generalize well to a realistic nonuniform traffic distribution not seen during training, thus outperforming the heuristics for this traffic. Visualization of the learned RWA policy reveals an RWA strategy that differs significantly from those of the heuristic baselines in terms of the distribution of services across channels and the distribution across links.

Stochastic RWA and Lightpath Rerouting in WDM Networks

In a telecommunication network, routing and wavelength assignment (RWA) is the problem of finding lightpaths for incoming connection requests. When facing a dynamic traffic, greedy assignment of lightpaths to incoming requests based on predefined deterministic policies leads to a fragmented network that cannot make use of its full capacity because of stranded bandwidth. At this point, service providers try to recover the capacity via a defragmentation process. We study this setting from two perspectives: (i) while granting the connection requests via the RWA problem and (ii) during the defragmentation process by lightpath rerouting. For both problems, we present the first two-stage stochastic integer programming model incorporating incoming request uncertainty to maximize the expected grade of service. We develop a decomposition-based solution approach, which uses various relaxations of the problem and a newly developed problem-specific cut family. Simulation of two-stage policies for a variety of instances in a rolling-horizon framework of 52 stages shows that our stochastic models provide high-quality solutions when compared with traditionally used deterministic ones. Specifically, the proposed provisioning policies yield improvements of up to 19% in overall grade of service and 20% in spectrum saving, while the stochastic lightpath rerouting policies grant up to 36% more requests, using up to just 4% more bandwidth spectrum.Summary of Contribution: For handling the intrinsic uncertainty of demand in the telecommunications industry, this paper proposes novel stochastic models and solution methodology for two fundamental problems in telecommunications at operational level: (i) routing and wavelength assignment (RWA) and (ii) lightpath rerouting problem. Despite the vast literature on the RWA problem, stochastic optimization has not been considered as a viable solution for resource allocation in optical networks. We propose two-stage stochastic programming models for both problems and design efficient decomposition-based solution methods that use various relaxations of the models and a new family of cutting planes. Our extensive and rigorous numerical experiments show the significant merit of incorporating uncertainty into decision making, as well as the effectiveness of the decomposition framework and our newly designed family of cuts in enhancing the solvability of both models. This work opens new avenues to explore where the powerful stochastic programming literature can be leveraged to make operational decisions in telecommunications problems, a field that currently relies mostly on deterministic and heuristic solution methods.

Application of Machine Learning in Routing and Wavelength Assignment: Literature Survey

This paper presents the survey of the prominent issue in optical networks is Routing and Wavelength Assignment (RWA), due to the heavy traffic in network, there will be a need for wavelength assignment to the track in that network. The RWA problem is resolved using the approach of Genetic Algorithm and Ant Colony Optimization Algorithm, wherein up until now is noticed to be better than other optimization algorithms. By using Deep Q-Networks, a type of reinforcement learning, in optimizing the problem in selection of the routing path and wavelength assignment in an optical mesh network.

Solving Rwa Problem in All-optical Networks Based on Optimized Ant Colony Algorithm

The information bandwidth growth can be achieved using optical networking technology. Optical fiber has been used as a physical means through many network technologies. Wavelength Division Multiplexing (WDM) has emerged as a promising technology to conquer the use of large-bandwidth in optical networks. In WDM network, the essential problem is to serve the load traffic represented by the requests that arrive at the network and need to be served. For serve the request, the network will determine a path paired with a specific wavelength used to send the request's data from source to the destination node. This problem is called the routing and wavelength assignment (RWA). In this work, Multi-Node Optimized Ant Colony Algorithm (M-NOACA) proposed and implemented to solve the RWA problem in all-optical networks by simulating traffic with the RWA algorithms. A performance measurements applied to study the optimization problem of the RWA, and apply a comparison with the classic algorithms. Determining the best collection of parameters for an ant-based algorithm to obtain the best performance remains an open issue, in this work, a study is done to introduce a new contribution to obtain the optimal setting of Ant Colony parameters used to solve the RWA problem.

Lightpath routing and wavelength assignment for static demand in translucent optical networks

Translucent optical networks use sparsely located regenerator nodes to increase the optical reach, otherwise limited by the physical layer impairments. Routing in translucent networks often causes the lightpath to traverse a fiber more than once, requiring the use of multiple wavelengths on a fiber for the same lightpath. Most of the routing and wavelength assignment (RWA) algorithms for static demand in translucent networks (termed static RWA) require loop-free routes for shortest path routing and also are agnostic to traffic load. In this paper, we address the problem of static RWA in translucent networks without using physical layer information and show how to route lightpaths on paths with a loop (i.e., not a simple path). We propose integer linear programming formulation to get the exact solutions to the static RWA problem. This work is the first one to optimally solve the static RWA problem for non-simple paths, providing the lower bound on the number of wavelengths and regeneration needed for static lightpath establishment when regeneration facilities are limited. We propose a heuristic algorithm based on the concept of Wardrop equilibrium, to adaptively equalize the mean delay along all the lightpath routes from source to destination. The proposed heuristic can not only accommodate the correlation between feasible lightpath routes but also account for the fact that alternate routes correspond to different levels of choice randomness. Wavelength assignment is done using graph coloring with branch-and-price method. Numerical results demonstrate that the proposed heuristic reduces the number of regenerators and wavelengths required to satisfy a given demand.

A Routing and Wavelength Assignment Algorithm Based on Two Types of LEO Constellations in Optical Satellite Networks

Research on LEO inter-satellite laser communication based on wavelength division multiplexing inter-satellite links and its routing and wavelength assignment (RWA) technology is an important way to solve the problem of low-latency, high-capacity, high-speed transmission, and low-cost on-orbit real-time routing of free-space optical communications. Since both the transmitting and receiving sides of the inter-satellite communication are high-speed moving satellites, the network topology in the whole inter-satellite communication process is time-varying. Therefore, based on this particularity, we propose the SpacePro constellation and combined the classical NeLS constellation for mathematical modeling, and the network topology and inter-satellite links are predicted and analyzed in their entire cycles. The RWA under the super satellite nodes with computation and storage functions algorithm (SCSA) is proposed and its effect is compared and analyzed in the wavelength resource requirement and connectivity. The results showed that the SCSA algorithm can save up to 50% in wavelength requirements, and the SpacePro constellation can achieve the same network connectivity effect with fewer on-board processors and wavelengths than NeLS. Satellite optical network node connectivity and wavelength demand are a trade-off problem. Studying the RWA problem in this scenario has a very critical reference for how the future satellite optical network performs wavelength usage configuration to help improve the performance of networks.

Performance Analysis of a Hierarchical Inter-Domain Provisioning Framework for Multi-Domain Software-Defined Optical Transport Networks

This paper analyzes the performance of a hierarchical inter-domain provisioning (HIP) framework for multi-domain software-defined optical transport networks (SD-OTNs). The challenge of this paper is to evaluate the performance and scalability of the HIP framework so that the framework can account for the complexity of the inter-domain routing and wavelength assignment (RWA) problem of the underlying OTNs. The framework is implemented in an experimental testbed to show the effectiveness of the HIP framework while ensuring seamless integration of multiple OTNs in a hierarchical control plane architecture. In addition to the experimental evaluations, the throughput, latency, and power metric of the framework based on a closed-form queueing model are evaluated analytically by considering the RWA problem of the underlying OTNs. The analytic results show that the HIP framework significantly improves the performance of a large-scale OTN with respect to the provisioning delay and throughput. Despite the marginal benefits of the blocking probability, the HIP framework permits enhanced scalability up to 24, 000 times by using a three-layer control plane architecture for multi-domain SD-OTNs.

A Memetic based Approach for Routing and Wavelength Assignment in Optical Transmission Systems

In optical networks, Routing and Wavelength Assignment (RWA) problem is one of the major optimization problems. This problem can be solved by different algorithms such as Genetic Algorithm (GA), Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), etc. Shuffled Frog Leaping Algorithm (SFLA) is implemented in the proposed work, to solve the RWA problem in long-haul optical networks. The goal is to use minimum number of wavelengths and to reduce the number of connection request rejections. Cost, number of wavelengths, hop count and blocking probability are the performance metrics considered in the analysis. Various wavelength assignment methods such as first fit, random, round robin, wavelength ordering and Four Wave Mixing (FWM) priority based wavelength assignment are used in the analysis using SFLA. Number of wavelengths, hop count, cost and setup time are included in the fitness function. The SFLA algorithm proposed, has been analyzed for different network loads and compared with the performance of genetic algorithm.

Hybrid Algorithm Based Effective Light Trail Creation in an Optical Networks

Abstract With the overwhelming use of the Internet, the wavelength division multiplexing (WDM) optical networks have become the major mode of communication for wide applications. Hence, the routing and wavelength assignment (RWA) for a given traffic in WDM networks is the chief challenge in optical networks. This paper presents the RWA problem in WDM networks using the hybrid algorithm of flower pollination (FP) and simulated annealing (SA) algorithm (FA+SA) with and without wavelength conversion capability at the nodes of the network. Comparative analysis with techniques presented in literature is also carried out, i. e. differential evolution algorithm (DEA), firefly algorithm (FA), particle swarm optimization with less number of informers (Psolbest), SA and genetic algorithm (GA). The results prove that hybrid algorithm of FP and SA is potentially more efficient than algorithms present in literature for the light path establishment in an optical network.

Improved Connection Establishment of Dynamic Traffic with Queue in WDM Optical Networks

Proper route selection between source and destination $$(s-d)$$ connection leads to efficient resource utilization which leads to the availability of resources for future call arrivals. Various choices are available for Routing and Wavelength Assignment (RWA) and every network demands a particular set of RWA to face least call blocking. Call blocking is an important issue in WDM network since it decides the provision of efficient service. In this paper, we have proposed the solution for RWA problem, efficient Wavelength Assignment Technique (WAT) and effect of call queuing in the network. We have studied and compared all sets of RWA over 14 nodes NSF network and found out that our proposed WAT works better in every set. Call blocking is a function of time and a slight change in time shows noticeable effects. We have shown the effect of call contention on WDM network and hence proposed the optimum value of it. Our simulation results for dynamic traffic show that optimal selection of RWA and contention window improve blocking of connections.

A routing and wavelength assignment scheme considering full optical carrier replication in multi-carrier-distributed optical mesh networks with wavelength reuse

This paper proposes a routing and wavelength assignment (RWA) scheme that considers full optical carrier replication to minimize the number of required wavelengths for wavelength-reusable multi-carrier-distributed (WRMD) mesh networks. Unlike the conventional wavelength division multiplexing networks where each node contains multiple laser diodes, the WRMD networks use a light source, called the multi-carrier light source, to ease the difficulty of controlling many light source devices. The optical carrier replication at any node of optical carrier or any end node of lightpath, called full optical carrier replication, improves the performance of the conventional schemes, which do not consider full optical carrier replication. This paper first formulates the RWA problem considering full optical carrier replication as an integer linear programming problem that minimizes the number of required wavelengths to satisfy the given lightpath setup requests. A heuristic RWA scheme is then proposed to solve the RWA problem in practical times. Simulation results show that our proposed heuristic RWA scheme for the WRMD network achieves a near-optimum number of wavelengths. In addition, it is able to reduce the number of required wavelengths for lightpath establishment, compared to the conventional scheme.

Multipoint to multipoint routing and wavelength assignment in multi-domain optical networks

In multi-point to multi-point (MP2MP) routing and wavelength assignment (RWA) problems, researchers usually assume the optical networks to be a single domain. However, the optical networks develop toward to multi-domain and larger scale in practice. In this context, multi-core shared tree (MST)-based MP2MP RWA are introduced problems including optimal multicast domain sequence selection, core nodes belonging in which domains and so on. In this letter, we focus on MST-based MP2MP RWA problems in multi-domain optical networks, mixed integer linear programming (MILP) formulations to optimally construct MP2MP multicast trees is presented. A heuristic algorithm base on network virtualization and weighted clustering algorithm (NV-WCA) is proposed. Simulation results show that, under different traffic patterns, the proposed algorithm achieves significant improvement on network resources occupation and multicast trees setup latency in contrast with the conventional algorithms which were proposed base on a single domain network environment.

Efficient Spectrum Utilization in Large Scale RWA Problems

While the routing and wavelength assignment (RWA) has been widely studied, a very few studies attempt to solve realistic size instances, namely, with 100 wavelengths per fiber and a few hundred nodes. Indeed, state of the art is closer to around 20 nodes and 30 wavelengths, regardless of what the authors consider, heuristics or exact methods with a very few exceptions. In this paper, we are interested in reducing the gap between realistic data sets and test bed instances that are often used, using exact methods. Even if exact methods may fail to solve in reasonable time very large instances, they can, however, output $\varepsilon $ -solutions with a very good and proven accuracy. The novelty of this paper is to exploit the observations that optimal solutions contain a very large number of light paths associated with shortest paths or $k$ -shortest paths with a small $k$ . We propose different RWA algorithms that lead to solve exactly or near exactly much larger instances than in the literature, i.e., with up to 150 wavelengths and 90 nodes. Extensive numerical experiments are conducted on both the static and dynamic incremental planning RWA problem.

An improved algorithm for RWA problem on sparse multifiber wavelength routed optical networks

Hitherto, several algorithms have been proposed for routing and wavelength assignment (RWA) problem on single or multifiber wavelength routed optical network (WRON) with or without wavelength converters. However, due to budget limit, we may equip only a few links in the network with multi fibers, and hence we have a sparse multifiber WRON (SM-WRON). Here, we consider the RWA problem on an SM-WRON without wavelength conversion. Different number of links are considered to equip with multi fibers to make an SM-WRON. Two basic techniques to select the required links to make them multifiber are random-choice and first-choice. The earlier one selects some links randomly and the later one selects the first numbered links. Here, in order to propose an improved algorithm, we define a cost for every link in the network, and then equip the most expensive links with multi fibers. The numerical results made on the well known benchmark networks, i.e., ARPANET and NSF topologies, show the proposed technique to be more efficient than the basic ones taking the blocking probability into account.

Solving routing and wavelength assignment problem with maximum edge-disjoint paths

The routing and wavelength assignment (RWA) problem in wave-length-division multiplexing optical networks is critically important for increasing the efficiency of wavelength-routed all-optical networks. Given the physical network structure and a set of connection requests, the problem aims to establishing routes for the requests and assigning a wavelength to each of them, subject to the wavelength continuous and wavelength clash constraints. The objective is to minimize he number of required wavelengths to satisfy all requests. The RWA problem was proven to be NP-hard and has been investigated for decades. In this paper, an algorithm based on the maximum edge-disjoint paths is proposed to tackle the RWA problem. Its performance is verified by experiments on some realistic network topologies. Compared with the state-of-the-art bin-packing based methods and the particle swarm optimization algorithm, the proposed method can find the best solution among all testing instances in reasonable computing time.

An improved least cost routing approach for WDM optical network without wavelength converters

Abstract Routing and wavelength assignment (RWA) problem has been an attractive problem in optical networks, and consequently several algorithms have been proposed in the literature to solve this problem. The most known techniques for the dynamic routing subproblem are fixed routing, fixed-alternate routing, and adaptive routing methods. The first one leads to a high blocking probability (BP) and the last one includes a high computational complexity and requires immense backing from the control and management protocols. The second one suggests a trade-off between performance and complexity, and hence we consider it to improve in our work. In fact, considering the RWA problem in a wavelength routed optical network with no wavelength converter, an improved technique is proposed for the routing subproblem in order to decrease the BP of the network. Based on fixed-alternate approach, the first k shortest paths (SPs) between each node pair is determined. We then rearrange the SPs according to a newly defined cost for the links and paths. Upon arriving a connection request, the sorted paths are consecutively checked for an available wavelength according to the most-used technique. We implement our proposed algorithm and the least-hop fixed-alternate algorithm to show how the rearrangement of SPs contributes to a lower BP in the network. The numerical results demonstrate the efficiency of our proposed algorithm in comparison with the others, considering different number of available wavelengths.

Genetic algorithm and tabu search algorithm for solving the static manycast RWA problem in optical networks

The static routing and wavelength assignment (RWA) problem in Optical Networks is a combinatorial optimization problem fit to iterative search methods. In this paper we deal with the static manycast RWA problem in optical networks and solve it by maximizing the number of manycast request established for a given number of wavelengths. In this article, we implement and compare the performance of two metaheuristics namely the GA "Genetic Algorithm" and the TSA "Tabu Search Algorithm". The proposed algorithms solve, approximately, the wavelength assignment problem and a backtracking approach is used to solve the routing problem. We first introduce our algorithms. We then evaluate and compare their performance. We corroborate our theoretical findings through extensive simulations. Representative empirical results show the accuracy of our GA and TSA.

Security-Aware Dynamic RWA for Reducing In-band and Out-of-band Jamming Attacks in WDM Optical Networks

The high data transfer capacities of current wavelength division multiplexing optical networks put large amounts of data at risk of getting corrupted in the presence of faults and attacks. A wide range of techniques for handling component failures in transparent optical networks are already available in the literature. In recent years, there is growing recognition of the need to develop suitable mechanisms for reducing the adverse effects of malicious attacks such as high-power jamming and tapping attacks. A number of recent papers have proposed static lightpath allocation approaches that take such security issues into consideration. However, most of these approaches consider the routing problem separately from the wavelength assignment problem. In this paper we propose a new security-aware scheme for the complete dynamic routing and wavelength assignment (RWA) problem. Unlike previous approaches, we consider both in-band and out-of-band attacks under dynamic traffic scenario and present an integer linear program (ILP) formulation with two possible objectives for solving the security-aware dynamic RWA problem. For larger networks we present an efficient heuristic algorithm SA-DRWA (Security-Aware Dynamic Routing and Wavelength Assignment) that aims to minimize both in-band and out-of-band attacks. To the best of our knowledge, this is the first such formulation to jointly consider in-band and out-of-band attacks, for dynamic traffic