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

WDM Mesh Networks with Dynamic Traffic

This article presents a mathematical model that results in a low-cost network design to satisfy a set of point-to-point demands that arrive and leave the network along of time. It considers the problem of routing working traffic and assigning wavelengths in an all-optical network avoiding if possible that wavelengths assignment changes and flow rerouting. The model allows to know when a reconfiguration/expansion is needed. The model provides a physical network configuration selecting a lowest cost set of components of the network (subnetworks and OXCs) with sufficient capacities to attend the demands and the required wavelengths in all time

A robust optimization approach to backup network design with random failures

This paper presents a scheme in which a dedicated backup network is designed to provide protection from random link failures. Upon a link failure in the primary network, traffic is rerouted through a preplanned path in the backup network. We introduce a novel approach for dealing with random link failures, in which probabilistic survivability guarantees are provided to limit capacity over-provisioning. We show that the optimal backup routing strategy in this respect depends on the reliability of the primary network. Specifically, as primary links become less likely to fail, the optimal backup networks employ more resource sharing amongst backup paths. We apply results from the field of robust optimization to formulate an ILP for the design and capacity provisioning of these backup networks. We then propose a simulated annealing heuristic to solve this problem for largescale networks, and present simulation results that verify our analysis and approach.National Science Foundation (U.S.) (grant CNS-0626781)National Science Foundation (U.S.) (grant CNS-0830961)United States. Defense Threat Reduction Agency (grant HDTRA1-07-1-0004)United States. Defense Threat Reduction Agency (grant HDTRA-09-1-005

Fast optical layer mesh protection using pre-cross-connected trails

Conventional optical networks are based on SONET rings, but since rings are known to use bandwidth inefficiently, there has been much research into shared mesh protection, which promises significant bandwidth savings. Unfortunately, most shared mesh protection schemes cannot guarantee that failed traffic will be restored within the 50 ms timeframe that SONET standards specify. A notable exception is the p-cycle scheme of Grover and Stamatelakis. We argue, however, that p-cycles have certain limitations, e.g., there is no easy way to adapt p-cycles to a path-based protection scheme, and p-cycles seem more suited to static traffic than to dynamic traffic. In this paper we show that the key to fast restoration times is not a ring-like topology per se, but rather the ability to pre-cross-connect protection paths. This leads to the concept of a pre-cross-connected trail or PXT, which is a structure that is more flexible than rings and that adapts readily to both path-based and link-based schemes and to both static and dynamic traffic. The PXT protection scheme achieves fast restoration speeds, and our simulations, which have been carefully chosen using ideas from experimental design theory, show that the bandwidth efficiency of the PXT protection scheme is comparable to that of conventional shared mesh protection schemes.Comment: Article has appeared in IEEE/ACM Trans. Networkin

Approximation Algorithms for Survivable Multicommodity Flow Problems with Applications to Network Design

Multicommodity flow (MF) problems have a wide variety of applications in areas such as VLSI circuit design, network design, etc., and are therefore very well studied. The fractional MF problems are polynomial time solvable while integer versions are NP-complete. However, exact algorithms to solve the fractional MF problems have high computational complexity. Therefore approximation algorithms to solve the fractional MF problems have been explored in the literature to reduce their computational complexity. Using these approximation algorithms and the randomized rounding technique, polynomial time approximation algorithms have been explored in the literature. In the design of high-speed networks, such as optical wavelength division multiplexing (WDM) networks, providing survivability carries great significance. Survivability is the ability of the network to recover from failures. It further increases the complexity of network design and presents network designers with more formidable challenges. In this work we formulate the survivable versions of the MF problems. We build approximation algorithms for the survivable multicommodity flow (SMF) problems based on the framework of the approximation algorithms for the MF problems presented in [1] and [2]. We discuss applications of the SMF problems to solve survivable routing in capacitated networks

Operating mesh-survivable WDM transport networks

All-optical networks with wavelength-division multiplexing (WDM) are considered to be a promising technology for next generation transport networks, as they can satisfy the growing bandwidth demand caused primarily due to an explosive growth of web-related services over the Internet. As the traffic demand increases, survivability becomes an indispensable requirement in WDM transport networks. This motivates the need for addressing failure restoration as an integral part of optical network design and operation. To date, the design problems have considered a static traffic demand aimed at optimizing the network capacity and cost, assuming various cost and survivability models. In this paper, we formulate three operational phases viz., initial call setup, medium-term reconfiguration when connections are blocked, and long-term reconfiguration to optimize resource utilization for the existing traffic, as a single Integer Linear Programming (ILP) optimization problem. This integrated framework is an attractive formulation that captures both capacity optimization and service disruption aspect in the problem formulation

Survivable MPLS Over Optical Transport Networks: Cost and Resource Usage Analysis

In this paper we study different options for the survivability implementation in MPLS over Optical Transport Networks (OTN) in terms of network resource usage and configuration cost. We investigate two approaches to the survivability deployment: single layer and multilayer survivability and present various methods for spare capacity allocation (SCA) to reroute disrupted traffic. The comparative analysis shows the influence of the offered traffic granularity and the physical network structure on the survivability cost: for high bandwidth LSPs, close to the optical channel capacity, the multilayer survivability outperforms the single layer one, whereas for low bandwidth LSPs the single layer survivability is more cost-efficient. On the other hand, sparse networks of low connectivity parameter use more wavelengths for optical path routing and increase the configuration cost, as compared with dense networks. We demonstrate that by mapping efficiently the spare capacity of the MPLS layer onto the resources of the optical layer one can achieve up to 22% savings in the total configuration cost and up to 37% in the optical layer cost. Further savings (up to 9 %) in the wavelength use can be obtained with the integrated approach to network configuration over the sequential one, however, at the increase in the optimization problem complexity. These results are based on a cost model with different cost variations, and were obtained for networks targeted to a nationwide coverage

Approximation Algorithms for Survivable Multicommodity Flow Problems with Applications to Network Design

Multicommodity flow (MF) problems have a wide variety of applications in areas such as VLSI circuit design, network design, etc., and are therefore very well studied. The fractional MF problems are polynomial time solvable while integer versions are NP-complete. However, exact algorithms to solve the fractional MF problems have high computational complexity. Therefore approximation algorithms to solve the fractional MF problems have been explored in the literature to reduce their computational complexity. Using these approximation algorithms and the randomized rounding technique, polynomial time approximation algorithms have been explored in the literature. In the design of high-speed networks, such as optical wavelength division multiplexing (WDM) networks, providing survivability carries great significance. Survivability is the ability of the network to recover from failures. It further increases the complexity of network design and presents network designers with more formidable challenges. In this work we formulate the survivable versions of the MF problems. We build approximation algorithms for the survivable multicommodity flow (SMF) problems based on the framework of the approximation algorithms for the MF problems presented in [1] and [2]. We discuss applications of the SMF problems to solve survivable routing in capacitated networks