Novel Adaptive Routing and Wavelength Assignment Algorithm for WDM Networks

This paper proposes the optimal design of lightpath Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexing (WDM) networks without wavelength conversion. We formulate RWA as a mixed Integer Linear Programming (ILP) problem where the objective is to minimize the cost of wavelength assignment to the fiber links in the network. The Lagrangean relaxation technique and the optimization-based heuristics are used to solve this problem. Two sets of computational experiments are performed to test the algorithms for the maximum carried traffic and minimum wavelength requirements in three different network topologies (GTE, ARPA, OCT network). Based on solution quality to the computational experiments, the error gaps between the upper bound and the lower bound are close enough that the near optimal solutions could be obtained. On the other hand, we also show that the solution quality degrade gracefully under more and more heavy traffic network environment. By assessing solution quality and the computational time, we propose the efficient and effective optimization-based algorithms based on the Lagrangean relaxation method for the RWA problem in the WDM networks without wavelength conversion.

In this paper, we compare performance of fixed-grid Wavelength Division Multiplexing (WDM) and Elastic Optical Networks (EONs) in dynamic provisioning of many-to-many (m2m) flows. Currently, with a growth of services relying on many-to-many communication paradigm such as distributed computing, inter-Data Center communication, content delivery networking or other requiring high-bandwidth in group communication, it is vital to deliver new solutions facilitating these demanding transmissions. Therefore, the authors investigate provisioning of m2m traffic in high-performance optical networks. This work focuses on dynamic Routing and Wavelength Assignment (RWA) problem in WDM networks as well as Routing and Spectrum Allocation (RSA) problem in EONs for m2m flows using replicated communication through auxiliary rendezvous servers.

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

In this paper, we address the problem of efficient routing and wavelength assignment (RWA) in multi-fiber wavelength division multiplexing (WDM) networks without wavelength translation, under dynamic traffic. We couple Dijkstra's shortest path algorithm with a suitable weight function which chooses optical paths based both on wavelength availability and multi-fiber segments. We compare our approach with other RWA schemes both for regular and irregular WDM multi-fiber network topologies in terms of blocking probability and overall link utilization.

The routing and wavelength assignment (RWA) problem for multipoint-to-point communications in all-optical wavelength division multiplexing (WDM) networks is investigated in this paper. Two efficient algorithms, namely Reverse Shortest Path Tree routing (RSPT) and k-Bounded Edge Disjoint Path routing (EDPR), are proposed. The problem of minimizing the total cost while establishing a multipoint-to-point session can be solved by RSPT algorithm in polynomial time. Nevertheless, EDPR algorithm produces a significant reduction in the maximum number of wavelengths required per link (i.e., the link stress) by a multipoint-to-point session. Simulations demonstrate the efficiencies of these two algorithms in supporting multipoint-to-point communications in WDM networks.

Throughput optimization and traffic engineering in Wavelength-Division Multiplexing (WDM) networks are usually treated as mono-objective optimization problems. In this paper, we provide a multi-objective Integer Linear Program (ILP) for the joint throughput optimization and traffic engineering problem. By simultaneously i) maximizing the throughput, ii) minimizing the resource consumption, and iii) balancing the traffic load, we demonstrate that better solutions than those of mono-objective approaches are obtained. We also present a distributed heuristic algorithm, which upper-bounds the per-route resource consumption and maximizes the throughput. Simulation results validate the proposed model and heuristic algorithm. Additionally, we present an ILP formulation for another well-known problem such as routing and wavelength assignment (RWA), and discuss the impact of modeling it as a multi-objective problem.

The routing and wavelength assignment (RWA) problem is a classic and challenging problem in wavelength-division multiplexing (WDM) optical networks and has shown to be NP-hard. This paper studies the min-RWA problem with the objective of minimizing the number of required wavelengths and presents a new powerful neighborhood called Shift-and-Shaking (SAS). The proposed SAS integrates a high-level shift move to change the wavelength of one lightpath and two low-level ejection chain-based shaking (ECS) procedures to find the best routings for the related lightpaths. This new neighborhood is embedded into a simple iterated local search algorithm, called SAS-ILS, for solving min-RWA. The proposed SAS-ILS is tested on three sets of totally 113 widely studied instances in the literature. Comparison with other state-of-the-art algorithms shows that the SAS-ILS is able to improve 22 previous best known results, while matching the best known results for the remaining ones within short computational time.

In an all-optical WDM network; optical fibers are used to transmit data followed by WDM technology. An optical fiber carries light along its length path at high rates and with little loss. Several wavelengths on a single fiber can be used to transfer data, when using wavelength-division multiplexing. In this way, several data transmissions at very high speed can take place on a single fiber. The routing and wavelength assignment (RWA) problem consists of finding a path and a wavelength for a set of data connections. The objective is typically to maximize the profit of established data by achieving as much as possible lightpath for transmitting optical signal (max-RWA). The RWA is NP-hard, thus much research has been conducted to finding a good way of approaching the RWA. This work mainly focuses on the analyzes work RWA problem based on integer linear programming (ILP) and reliable heuristics for variant topology of WDM networks. For performance analysis heuristics method as well as others variants of solution for RWA problem also had been implemented which results give some interesting observation about resources as well as optimal solution.

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 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.

This paper studies the routing and wavelength assignment (RWA) problem in wavelength-routed all-optical networks with dynamic traffic demand. In this letter, we model the link state transition as a birth and death process. With the proposed Markov model, the path blocking probability can be determined based on the current link state and the potential link load information, and then, we establish lightpath on the least congested route. The simulation result shows that compared with other adaptive routing algorithms, the proposed algorithm achieves much better blocking performance.

This paper addresses the problem of routing and wavelength assignment (RWA) in multifiber WDM networks with limited resources. Given a traffic matrix, the number of fibers per link, and the number of wavelengths a fiber can support, we seek to maximize the carried traffic of connections. We formulate the problem as an integer linear program (ILP), and show that the lightpaths selected by this formulation can indeed be established by properly configuring the optical switches. An upper bound on the carried traffic can be computed by solving the linear programming (LP)-relaxation of the ILP formulation. It is shown that this bound can be also computed exactly, and in polynomial-time, by solving a significantly simplified LP which considers only one wavelength. The bound can, thus, easily scale to an arbitrarily large number of wavelengths. Furthermore, we demonstrate that any instance of the RWA problem is also an instance of the more general maximum coverage problem. This allows us to take a greedy algorithm for maximum coverage and obtain an algorithm which provides solutions for the RWA problem that are guaranteed to be within a factor of (1-(1/e)) of the optimal solution. Each iteration of the greedy algorithm selects a set of lightpaths that realizes, using one wavelength, the maximum number of connection requests not previously realized. Computational results confirm the high efficiency of our proposed algorithm.

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 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 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.