Genetic algorithm for the topological design of survivable optical transport networks

We develop a genetic algorithm for the topological design of survivable optical transport networks with minimum capital expenditure. Using the developed genetic algorithm we can obtain near-optimal topologies in a short time. The quality of the obtained solutions is assessed using an integer linear programming model. Two initial population generators, two selection methods, two crossover operators, and two population sizes are analyzed. Computational results obtained using real telecommunications networks show that by using an initial population that resembles real optical transport networks a good convergence is achieved

Multiobjective evolutionary algorithms for intradomain routing optimization

Evolutionary Algorithms (EAs) have been used to develop methods for Traffic Engineering (TE) over IP-based networks in the last few years, being used to reach the best set of link weights in the configuration of intra-domain routing protocols, such as OSPF. In this work, the multiobjective nature of a class of optimization problems provided by TE with Quality of Service constraints is identified. Multiobjective EAs (MOEAs) are developed to tackle these tasks and their results are compared to previous approaches using single objective EAs. The effect of distinct genetic representations within the MOEAs is also explored. The results show that the MOEAs provide more flexible solutions for network management, but are in some cases unable to reach the level of quality obtained by single objective EAs. Furthermore, a freely available software application is described that allows the use of the mentioned optimization algorithms by network administrators, in an user-friendly way by providing adequate user interfaces for the main TE tasks.FCT - project ref. PTDC/EIA-EIA/115176/2009; grant UMINHO/BII/061/200

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

A Network Recovery Strategy Scheme Based on Network Failure Scenarios and Topologies

Network failures happen frequently. There is a need for recovery mechanisms to reduce service interruption. Recovery mechanismsâ advantages and disadvantages are described extensively based on their characteristics and performances. However, it is more desirable that network recovery strategies are chosen based on failure scenarios and topologies. In this paper, we propose a recovery scheme and focus on networks whose paths and resources from source to destination nodes are computed and negotiated primarily at source nodes, Ingress Label Switched Router (LSR), which are the case for Generalized Multiprotocol Label Switching (GMPLS) networks. Choosing proper network recovery mechanisms depends on many parameters such as distance of failure from source node, degree distribution of nodes, availabilities of alternative paths, and maximum allowed-hopcount increase in alternative paths. Three recovery mechanisms: Haskin, Global and Local Protection are compared with the proposed restoration scheme. By changing parameters on appropriate ranges and by using probability of received data packet at the destination node, e.g. probability of error as one of the performance criteria, we can make a fair judgment on choosing a network strategy by considering available network parameters and topology

Sub-graph based Multicast Protection in WDM Networks: A Multi/Many-Objective Evolutionary Algorithms approaches

In this paper is addressed the multicast routing-and-protection, and wavelength assignment (MRPWA) problem which is critical for the success of applications point-multipoint in WDM networks. Basically, it is proposed the design of the primary and protection multicast routes, where the resources protection are based on sub-graph protection strategy subject to the quality requirements of the QoP protection: dedicated (1 + 1), shared (M: N) and better effort (without protection). In this way, NSGA-II and NSGA-III, evolutionary algorithms, are applied to MRPWA considering multi- and many-objectives optimization context, respectively. The evolutionary algorithms optimize simultaneously: (i) the total number of links used, (ii) the number of wavelength converters, (iii) the number of splitter nodes, and (iv) the number of destinations served-and-protected. Considering Hyper-volume measure, the experimental tests on a set of instances indicate that the protection approach based on sub-graph proves to be promising in comparison to the dualtree protection strategy. On the other hand, the evolutionary technique oriented to many-objectives (NSGA-III) is more convenient than the oriented towards multi-objectives (NSGA-II) in the study problem.XIII Workshop Arquitectura, Redes (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Sub-graph based Multicast Protection in WDM Networks: A Multi/Many-Objective Evolutionary Algorithms approaches

In this paper is addressed the multicast routing-and-protection, and wavelength assignment (MRPWA) problem which is critical for the success of applications point-multipoint in WDM networks. Basically, it is proposed the design of the primary and protection multicast routes, where the resources protection are based on sub-graph protection strategy subject to the quality requirements of the QoP protection: dedicated (1 + 1), shared (M: N) and better effort (without protection). In this way, NSGA-II and NSGA-III, evolutionary algorithms, are applied to MRPWA considering multi- and many-objectives optimization context, respectively. The evolutionary algorithms optimize simultaneously: (i) the total number of links used, (ii) the number of wavelength converters, (iii) the number of splitter nodes, and (iv) the number of destinations served-and-protected. Considering Hyper-volume measure, the experimental tests on a set of instances indicate that the protection approach based on sub-graph proves to be promising in comparison to the dualtree protection strategy. On the other hand, the evolutionary technique oriented to many-objectives (NSGA-III) is more convenient than the oriented towards multi-objectives (NSGA-II) in the study problem.XIII Workshop Arquitectura, Redes (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Fault Tolerant Dense Wavelength Division Multiplexing Optical Transport Networks, Journal of Telecommunications and Information Technology, 2009, nr 1

Design of fault tolerant dense wavelength division multiplexing (DWDM) backbones is a major issue for service provision in the presence of failures. The problem is an NP-hard problem. This paper presents a genetic algorithm based approach for designing fault tolerant DWDM optical networks in the presence of a single link failure. The working and spare lightpaths are encoded into variable length chromosomes. Then the best lightpaths are found by use of a fitness function and these are assigned the minimum number of wavelengths according to the problem constraints using first-fit (FF) algorithm. The proposed approach has been evaluated for dedicated path protection architecture. The results, obtained from the ARPA2 test bench network, show that the method is well suited to tackling this complex and multi-constraint problem

Optimization of traffic flows in multiservice telecomunications networks

This dissertation investigates routing optimization in IP telecommunication networks, under normal working conditions as well as under failure conditions. The main objectives of the present optimization procedure are the minimization of the maximum link utilization in the network and to provide a configuration that guarantees a 100% survivability degree. Traditionally two different steps are used to achieve this goal. The first one aims to solve the well known “General Routing Problem (GRP)” in order to find the optimal routing network configuration and, successively, a set of “optimal” backup paths is found in order to guarantee network survivability. Furthermore, traditional survivable techniques assume that the planning tasks are performed in a network control center while restoration schemes are implemented distributively in network nodes. In this dissertation innovative linear programming models are presented that, making use of the Multi Protocol Label Switching – Traffic Engineering (MPLS-TE) techniques and IS-IS/OSPF IP routing protocol, melt routing and survivability requirements. The models are extremely flexible, thus it is possible to improve the objective function in order to fit itself to newer applications and/or traffic typologies. The models presented in this dissertation help Internet Service Providers to optimize their network resources and to guarantee connectivity in case of failure, while still be able to offer a good quality of service