Revenue-driven Lightpaths Provisioning over Optical WDM Networks Using Bee Colony Optimization

Recently, machine learning (ML) has attracted the attention of both researchers and practitioners to address several issues in the optical networking field. This trend has been mainly driven by the huge amount of available data (i.e., signal quality indicators, network alarms, etc.) and to the large number of optimization parameters which feature current optical networks (such as, modulation format, lightpath routes, transport wavelength, etc.). In this paper, we leverage the techniques from the ML discipline to efficiently accomplish the routing and wavelength assignment (RWA) for an input traffic matrix in an optical WDM network. Numerical results show that near-optimal RWA can be obtained with our approach, while reducing computational time up to 93% in comparison to a traditional optimization approach based on integer linear programming. Moreover, to further demonstrate the effectiveness of our approach, we deployed the ML classifier into an ONOS-based software defined optical network laboratory testbed, where we evaluate the performance of the overall RWA process in terms of computational time.

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

The method in which Routing and Wavelength Assignment (RWA) of connection requests is performed in optical WDM networks, can appreciably affect resource consumption. The blocking probability for lightpath requests increases significantly with increase in resource consumption. Thus the method of performing RWA should be such that it minimizes consumption of network resources. RWA in all-optical networks is an NP-Complete problem. This paper proposes six new heuristic algorithms for static RWA in all-optical mesh networks that are not only efficient in terms of resource conservation but can also solve the RWA problem effectively in polynomial time. Comparisons show that the proposed algorithms perform better than some earlier well-known strategies.

In optical WDM networks, transmission of information along optical lines is advantageous since it has high transmission capacity, scalability, feasibility and also high reliability. But large amount of information is being carried; any problem during transmission can lead to severe damage to the data being carried. Hence it is essential to consider the routing as well as the wavelength assignment problems and then develop a combined solution for both the problems. In this paper, we propose to develop a routing and wavelength assignment algorithm for selecting the suitable alternate path for the data packets transmission. Two stages are based on the available bandwidth and the number of wavelength used in the link as construction of alternate paths, route and wavelength selection. In proposed work, Adaptive Routing and First-Fit Wavelength Assignment (AR-FFWA) algorithm to be used. For each pair of source and destination, the path with the minimum granularity values are selected as the primary path for data transmission, allocating the sufficient wavelength and the performances will be evaluated by using ns-2 simulation models. When we compared to existing system the overall blocking probability will be reduced to too low.

Adaptive FEC-based lightpath routing and wavelength assignment in WDM optical networks

While a session request is assigned to a wavelength-routed optical WDM networks, which are circuit-switched in nature, the challenge of routing and wavelength assignment (RWA) is to calculate the optimal path between two nodes, and further is to assign an available set of wavelengths along this path. An algorithm called Total wavelengths and Expected available wavelengths (TEW) proposed by Pavarangkoon et. al. in order to achieve effective routing and wavelength assignment formulates a link weight function and considers this as the main factor for route selection. This function is calculated by using a determination factor of the number of wavelengths that are being used currently and are supposed to be available after a certain time. However, this algorithm tends to overload paths with smaller weights and higher utilization while lightly loaded paths with slightly lower capacities may remain unused. In this paper, propose an improvement to the TEW algorithm by incorporating the frequency of usage of the paths in the weight function and running Dijkstra’s shortest path algorithm to choose paths that have more total and expected available wavelengths and less frequency of usage. The proposed algorithm is called as Countered Total wavelengths and Expected available wavelengths (CTEW) algorithm. The impact of the proposed algorithm on blocking probability is investigated by means of computer simulation and by comparing it with TEW algorithm. The results show that the proposed algorithm can achieve better performance in terms of blocking probability.

Routing and wavelength assignment vs. EDFA reliability performance in optical backbone networks: An operational cost perspective

In this paper we investigate traffic-engineering issues in Wavelength Division Multiplexing (WDM) all- optical networks. In such networks, the wavelength continuity constraint along with the wavelength clash constraint, lead to poor network performances when dealing with the lightpath provisioning problem. The impact of these constraints is especially severe when traffic demands are unpredictable and characterized by random arrivals and departures. In order to alleviate the impact of these constraints, we propose to employ intentional/active rerouting. Active lightpath rerouting is to intentionally reroute already established lightpaths, during their life period, so as to achieve a better blocking performance. We here assume that due to the large geographic area an optical WDM network can cover, upgrading such a network to support the huge demand for network bandwidth can be costly. Thereby, it is extremely important for network operators to apply traffic-engineering strategies to cost-effectively optimize network throughput. Two new routing and wavelength assignment (RWA) algorithms applying intentional rerouting are proposed. Both algorithms dynamically reroute some already established lightpaths from longer paths to vacant shorter ones so as to reduce the network resources consumption and hence improve the network throughput. The first algorithm, namely, Timer-Based Active Lightpath Rerouting (TB-ALR) initiates the rerouting procedure every time a timer expires. The second algorithm, namely, Sequential Routing with Active Lightpath Rerouting (SeqRwALR) initiates the rerouting procedure when a connection leaves and its lightpaths are released. To the best of our knowledge, our global approach has not already been investigated in the literature. Simulation results show that the proposed active rerouting algorithms yield much lower connection rejection ratios than rerouting algorithms previously presented in the literature while rerouting a small number of already established lightpaths. By rerouting a small number of existing lightpaths, we hope that the disruption period incurred due to rerouting is minimized.

The widespread deployment of wireless telecommunication networks and growing Internet traffic globally leads to a substantial increase in signal traffic demands in fiber optic networks. This demand surge places significant pressure on the survivability of optical networks, specifically when faced with fiber cable failures that prevent failed optical fibers from satisfying connection requests. To address this challenge, in this paper, we consider integrated planning of regenerator installation, optical connection routing, and wavelength assignment (RWA) for wavelength division multiplexing (WDM) optical networks under link failures. To the best of our knowledge, we are the first to consider such an integrated problem. We minimize the number of backup regenerators required to fulfill all connection requests under all potential link failures while accounting for the wavelength and routing constraints. We formulate the problem as an integer program, while its size exponentially increases with the network size by nature. To solve large-scale instances for practical uses in the industry, we propose efficient algorithms to generate near-optimal solutions that are practically implementable. We perform extensive numerical experiments to demonstrate the effectiveness of our approach in solving real-world instances provided by our industry partners. The results show that our approach can efficiently obtain high-quality solutions while ensuring a minimal increase in backup regenerators as the network grows. Our solutions also offer valuable insights into planning a cost-effective and reliable fiber optic network for network operators.

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.

The advent of WDM technology has resulted in transmission capacities that have increased manifold in recent years. The most common architecture used for establishing communication in WDM optical networks is wavelength routing, where data are transmitted over all-optical WDM channels, called lightpaths, which may span multiple consecutive fibers. A lightpath is realized by determining a path between the source and the destination and allocating a free wavelength on all the links of the path. The selection of the path and the wavelength to be used by a lightpath is an important optimization problem, known as the routing and wavelength assignment (RWA) problem (Ramaswami & Sivarajan, 1995). In the absence of wavelength conversion, a lightpath must be assigned a common wavelength on each link it traverses; this restriction is referred to as the wavelength continuity constraint. However, two lightpaths may occupy the same wavelength, as long as they use disjoint sets of links; this property is known as wavelength reuse. The RWA problem is usually considered under two alternative traffic models. Static Lightpath Establishment (SLE) addresses the case where the set of connections is known in advance and Dynamic Lightpath Establishment (DLE) considers the case where connection requests arrive randomly, over an infinite time horizon, and are served one-by-one.

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.

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.

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.

Solving multi-objective routing and wavelength assignment in WDM network using hybrid evolutionary computation approach