A Novel Solution to the Dynamic Routing and Wavelength Assignment Problem in Transparent Optical Networks

We present an evolutionary programming algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in optical wavelength-division multiplexing (WDM) networks under wavelength continuity constraint. We assume an ideal physical channel and therefore neglect the blocking of connection requests due to the physical impairments. The problem formulation includes suitable constraints that enable the algorithm to balance the load among the individuals and thus results in a lower blocking probability and lower mean execution time than the existing bio-inspired algorithms available in the literature for the DRWA problems. Three types of wavelength assignment techniques, such as First fit, Random, and Round Robin wavelength assignment techniques have been investigated here. The ability to guarantee both low blocking probability without any wavelength converters and small delay makes the improved algorithm very attractive for current optical switching networks.Comment: 12 Pages, IJCNC Journal 201

Multi-Objective Integer Linear Programming Model for Path Optimization in Wavelength Division Multiplexing Networks

Optical networks with Wavelength Division Multiplexing (WDM) has been the solution for the need of increasing bandwidth demand. In this kind of networks the fiber link is divided into a number of channels. In each channel a light wave of a particular wavelength can be transmitted. So, in a single fiber more than one light waves of different wavelengths can be transmitted simultaneously with the use of multiplexers and demultiplexers. In WDM optical networks there are two problems. First one is providing a path for a source to destination pair, and second one providing a wavelength to the path selected. The former is called routing problem and the latter is called wavelength assignment problem. Combining both the problems, it is called Routing and Wavelength Assignment (RWA) Problem. The RWA problem belongs to NP class, i.e. it can not be solved in polynomial time. So, different heuristic approaches are used to find a (sub)optimal solution for the problem. An ILP model may be used to solve the RWA problem considering various parameters of the optical network like congestion, total route length, number of amplifiers used etc. In this project an ILP is designed for the RWA problem and is solved using genetic algorithm to find an optimal solution. The simulation is carried out on Advanced Research Project Agency NETwork (ARPANET) and National Science Foundation Network(NSFNET)

Review of routing and wavelength assignment problem

In today’s internet world there is a growing demand of network bandwidth. Where traditional copper fibers offer very less bandwidth, optical fibers can offer very lager bandwidth. So, there is a growing sense of using optical fibers. Optical networks generally use wavelength division multiplexing (WDM) technique, which is the backbone of future generation internet. In WDM networks fibers are logically divided into non-interfering, circuit-switched communication channels. In optical network Routing and Wavelength Assignment (RWA) problem is a typical problem. This can be seen as a conjunction of two problems, one is Routing and other one is Wavelength Assignment. First one finds a route from source to destination for requested connection and the next one assigns a wavelength to this route. The nature of RWA problem is NP-complete. Hence, heuristic approaches suits well for this class of problems. RWA problem can be formulated as Integer linear programming (ILP) problem. This type of problem focuses on optimizing a single objective. Here objectives may be minimizing the number of amplifiers or maximizing the number of connections or minimizing the number of wavelength used. But our primary objective in RWA problem is to establish a loop free path which minimizes the crosstalk. To achieve this objective we are taking the help of genetic algorithm (GA). Congestion among the individual lightpath request will be the parameter for the application of genetic algorithm

Study of Routing and Wavelength Assignment problem and Performance Analysis of Genetic Algorithm for All-Optical Networks

All-optical networks uses the concept of wavelength division multiplexing (WDM). The problem of routing and wavelength assignment (RWA) is critically important for increasing the efficiency of wavelength routed All-optical networks. For the given set of connections, the task of setting up lightpaths by routing and assigning a wavelength to each connection is called routing and wavelength allocation problem. In work to date, the problem has been formulated as integer linear programming problem. There are two variations of the problem: static and dynamic, in the static case, the traffic is known where as in dynamic case, connection request arrive in some random fashion. Here we adopt the static view of the problem. We have studied the Genetic Algorithm to solve the RWA problem and also we studied a modified Genetic Algorithm with reference to the basic model. We studied a novel opimization problem formulations that offer the promise of radical improvements over the existing methods. We adopt a static view of the problem and saw new integer- linear programming formulations, which can be addressed with highly efficient linear programming methods and yield optimal or near-optimal RWA policies. All-optical WDM networks are chracterized by multiple metrics (hop-count, cost, delay), but generally routing protocols only optimize one metric, using some variant shortest path algorithm (e.g., the Dijkstra, all-pairs and Bellman-ford algorithms). The multicriteria RWA problem has been solved combining the relevant metrics or objective functions. The performance of RWA algorithms have been studied across the different standard networks. The performance of both the algorithms are studied with respect to the time taken for making routing decision, number of wavelengths required and cost of the requested lightpaths. It has been observed that the modified genetic algorithm performed better than the existing algorithm with respect to the time and cost parameters

Particle swarm optimization for routing and wavelength assignment in next generation WDM networks.

PhDAll-optical Wave Division Multiplexed (WDM) networking is a promising technology for long-haul backbone and large metropolitan optical networks in order to meet the non-diminishing bandwidth demands of future applications and services. Examples could include archival and recovery of data to/from Storage Area Networks (i.e. for banks), High bandwidth medical imaging (for remote operations), High Definition (HD) digital broadcast and streaming over the Internet, distributed orchestrated computing, and peak-demand short-term connectivity for Access Network providers and wireless network operators for backhaul surges. One desirable feature is fast and automatic provisioning. Connection (lightpath) provisioning in optically switched networks requires both route computation and a single wavelength to be assigned for the lightpath. This is called Routing and Wavelength Assignment (RWA). RWA can be classified as static RWA and dynamic RWA. Static RWA is an NP-hard (non-polynomial time hard) optimisation task. Dynamic RWA is even more challenging as connection requests arrive dynamically, on-the-fly and have random connection holding times. Traditionally, global-optimum mathematical search schemes like integer linear programming and graph colouring are used to find an optimal solution for NP-hard problems. However such schemes become unusable for connection provisioning in a dynamic environment, due to the computational complexity and time required to undertake the search. To perform dynamic provisioning, different heuristic and stochastic techniques are used. Particle Swarm Optimisation (PSO) is a population-based global optimisation scheme that belongs to the class of evolutionary search algorithms and has successfully been used to solve many NP-hard optimisation problems in both static and dynamic environments. In this thesis, a novel PSO based scheme is proposed to solve the static RWA case, which can achieve optimal/near-optimal solution. In order to reduce the risk of premature convergence of the swarm and to avoid selecting local optima, a search scheme is proposed to solve the static RWA, based on the position of swarm‘s global best particle and personal best position of each particle. To solve dynamic RWA problem, a PSO based scheme is proposed which can provision a connection within a fraction of a second. This feature is crucial to provisioning services like bandwidth on demand connectivity. To improve the convergence speed of the swarm towards an optimal/near-optimal solution, a novel chaotic factor is introduced into the PSO algorithm, i.e. CPSO, which helps the swarm reach a relatively good solution in fewer iterations. Experimental results for PSO/CPSO based dynamic RWA algorithms show that the proposed schemes perform better compared to other evolutionary techniques like genetic algorithms, ant colony optimization. This is both in terms of quality of solution and computation time. The proposed schemes also show significant improvements in blocking probability performance compared to traditional dynamic RWA schemes like SP-FF and SP-MU algorithms

Virtualisation and resource allocation in MECEnabled metro optical networks

The appearance of new network services and the ever-increasing network traffic and number of connected devices will push the evolution of current communication networks towards the Future Internet. In the area of optical networks, wavelength routed optical networks (WRONs) are evolving to elastic optical networks (EONs) in which, thanks to the use of OFDM or Nyquist WDM, it is possible to create super-channels with custom-size bandwidth. The basic element in these networks is the lightpath, i.e., all-optical circuits between two network nodes. The establishment of lightpaths requires the selection of the route that they will follow and the portion of the spectrum to be used in order to carry the requested traffic from the source to the destination node. That problem is known as the routing and spectrum assignment (RSA) problem, and new algorithms must be proposed to address this design problem. Some early studies on elastic optical networks studied gridless scenarios, in which a slice of spectrum of variable size is assigned to a request. However, the most common approach to the spectrum allocation is to divide the spectrum into slots of fixed width and allocate multiple, consecutive spectrum slots to each lightpath, depending on the requested bandwidth. Moreover, EONs also allow the proposal of more flexible routing and spectrum assignment techniques, like the split-spectrum approach in which the request is divided into multiple "sub-lightpaths". In this thesis, four RSA algorithms are proposed combining two different levels of flexibility with the well-known k-shortest paths and first fit heuristics. After comparing the performance of those methods, a novel spectrum assignment technique, Best Gap, is proposed to overcome the inefficiencies emerged when combining the first fit heuristic with highly flexible networks. A simulation study is presented to demonstrate that, thanks to the use of Best Gap, EONs can exploit the network flexibility and reduce the blocking ratio. On the other hand, operators must face profound architectural changes to increase the adaptability and flexibility of networks and ease their management. Thanks to the use of network function virtualisation (NFV), the necessary network functions that must be applied to offer a service can be deployed as virtual appliances hosted by commodity servers, which can be located in data centres, network nodes or even end-user premises. The appearance of new computation and networking paradigms, like multi-access edge computing (MEC), may facilitate the adaptation of communication networks to the new demands. Furthermore, the use of MEC technology will enable the possibility of installing those virtual network functions (VNFs) not only at data centres (DCs) and central offices (COs), traditional hosts of VFNs, but also at the edge nodes of the network. Since data processing is performed closer to the enduser, the latency associated to each service connection request can be reduced. MEC nodes will be usually connected between them and with the DCs and COs by optical networks. In such a scenario, deploying a network service requires completing two phases: the VNF-placement, i.e., deciding the number and location of VNFs, and the VNF-chaining, i.e., connecting the VNFs that the traffic associated to a service must transverse in order to establish the connection. In the chaining process, not only the existence of VNFs with available processing capacity, but the availability of network resources must be taken into account to avoid the rejection of the connection request. Taking into consideration that the backhaul of this scenario will be usually based on WRONs or EONs, it is necessary to design the virtual topology (i.e., the set of lightpaths established in the networks) in order to transport the tra c from one node to another. The process of designing the virtual topology includes deciding the number of connections or lightpaths, allocating them a route and spectral resources, and finally grooming the traffic into the created lightpaths. Lastly, a failure in the equipment of a node in an NFV environment can cause the disruption of the SCs traversing the node. This can cause the loss of huge amounts of data and affect thousands of end-users. In consequence, it is key to provide the network with faultmanagement techniques able to guarantee the resilience of the established connections when a node fails. For the mentioned reasons, it is necessary to design orchestration algorithms which solve the VNF-placement, chaining and network resource allocation problems in 5G networks with optical backhaul. Moreover, some versions of those algorithms must also implements protection techniques to guarantee the resilience system in case of failure. This thesis makes contribution in that line. Firstly, a genetic algorithm is proposed to solve the VNF-placement and VNF-chaining problems in a 5G network with optical backhaul based on star topology: GASM (genetic algorithm for effective service mapping). Then, we propose a modification of that algorithm in order to be applied to dynamic scenarios in which the reconfiguration of the planning is allowed. Furthermore, we enhanced the modified algorithm to include a learning step, with the objective of improving the performance of the algorithm. In this thesis, we also propose an algorithm to solve not only the VNF-placement and VNF-chaining problems but also the design of the virtual topology, considering that a WRON is deployed as the backhaul network connecting MEC nodes and CO. Moreover, a version including individual VNF protection against node failure has been also proposed and the effect of using shared/dedicated and end-to-end SC/individual VNF protection schemes are also analysed. Finally, a new algorithm that solves the VNF-placement and chaining problems and the virtual topology design implementing a new chaining technique is also proposed. Its corresponding versions implementing individual VNF protection are also presented. Furthermore, since the method works with any type of WDM mesh topologies, a technoeconomic study is presented to compare the effect of using different network topologies in both the network performance and cost.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

A new proposal of an efficient algorithm for routing and wavelength assignment in optical networks.

The routing and wavelength assignment (RWA) algorithms used in optical networks are critical to achieve good network performance. However, despite several previous studies to optimize the RWA, which is classified as an NP-Hard, it seems that there is not, a priori, any solution that would lead to standardization of this process. This article presents the proposed RWA algorithm based on a Generic Objective Function (GOF) which aims to establish a base from which it is possible to develop a standard or multiple standards for optical networks. The GOF algorithm introduces the concept of implicit constraint, which guarantees a simple solution to a problem not as trivial as the RWA

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT