Sonet Network Design Problems

This paper presents a new method and a constraint-based objective function to solve two problems related to the design of optical telecommunication networks, namely the Synchronous Optical Network Ring Assignment Problem (SRAP) and the Intra-ring Synchronous Optical Network Design Problem (IDP). These network topology problems can be represented as a graph partitioning with capacity constraints as shown in previous works. We present here a new objective function and a new local search algorithm to solve these problems. Experiments conducted in Comet allow us to compare our method to previous ones and show that we obtain better results

Open Source Solutions for Optimization on Linux Clus- ters

Abstract: Parallel implementation of optimization algorithms is an alternative and effective paradigm to speed up the search for solutions of optimization problems. Currently a Linux Cluster is probably the best technological solution available considering both the overall system performance and its cost. Open Source community offers to researchers a set of software tools for setting up clusters and to optimize their performance. The aim of this paper is to review the open source tools are useful to build a cluster which efficiently runs parallel optimization algorithms. Particular attention is given to the OpenMosix approach to scalable computing. Keywords: Open Source, Linux Cluster, Optimization, OpenMosix, Dynamic Load Balancing INTRODUCTION Although (sequential) optimization algorithms have reached a sophisticated level of implementation allowing good computational results for a large variety of optimization problems, usually the running time required to explore the solution space associated to optimization problems can be very large With the diffusion of parallel computers and fast communication networks, parallel implementation of optimization algorithms can be an alternative and effective paradigm to speed up the search for solutions of optimization problems

Efficient communication using multiple cycles and multiple channels

Initially, the use of optical fiber in networks was to create point-to-point links. Optical paths were not altered once they were setup. This limits the ability of the network to respond to changing traffic demands. There were expensive solutions to handle dynamic traffic. One could set up multiple paths for additional traffic. Alternately, traffic that did not have a dedicated optical path needed to be received, the next hop found electronically, and then transmitted again. Current research in optical networking is looking to minimize or even eliminate electronic packet processing in the network. This will reduce the numbers of transmitters, receivers, and processing hardware needed in the network. If a signal can be kept entirely optical, new signal formats can be added to the network by only upgrading systems sending or receiving the new format. Research is currently looking at hardware designs to support electrically changing optical paths, and algorithms to route the optical paths. The topic of this work is the routing algorithms. We wish to keep cost as low as possible, while being able to recover quickly from or completely hide hardware failures. Several strategies exist to meet these expectations that involve a mix of handing routing and failure at the optical or at the electronic layer. This dissertation considers the use of cycles or rings in both establishing optical connections in response to connection requests, and electronic routing on optical cycle\u27s setup when a network is built. Load balancing is an important issue for both approaches. In this dissertation we provide heuristics and integer linear program (ILP) that can be used to find cycles in a network. We report on experiments showing the effectiveness of the heuristics. Simulations show the importance of load balancing. In the case of electronic routing, we setup cycles in the network which allow nodes on the cycle to communicate with each other. We select cycles so that they have two properties. One property is that all node pairs appear on at least one cycle. The other property is that each cycle contains a cyclical quorum. The first property allows for a network to support all-to-all communication entirely in the optical domain. The second property allows for quorum based distributed systems to send a message to an entire quorum in an all optical one-to-many connection. The use of quorums makes distributed systems efficient at tasks such as coordinating mutual exclusion or database replication. There is a need for the optical layer of the network to provide support for keeping latency of this type of communication low because as designers have scarified the benefits of using quorums in higher latency networks. Combined with light trails, cycles based on quorums requires fewer transmitter and receivers than light-paths to support all-to-all traffic

Improvements on the bees algorithm for continuous optimisation problems

This work focuses on the improvements of the Bees Algorithm in order to enhance the algorithm’s performance especially in terms of convergence rate. For the first enhancement, a pseudo-gradient Bees Algorithm (PG-BA) compares the fitness as well as the position of previous and current bees so that the best bees in each patch are appropriately guided towards a better search direction after each consecutive cycle. This method eliminates the need to differentiate the objective function which is unlike the typical gradient search method. The improved algorithm is subjected to several numerical benchmark test functions as well as the training of neural network. The results from the experiments are then compared to the standard variant of the Bees Algorithm and other swarm intelligence procedures. The data analysis generally confirmed that the PG-BA is effective at speeding up the convergence time to optimum. Next, an approach to avoid the formation of overlapping patches is proposed. The Patch Overlap Avoidance Bees Algorithm (POA-BA) is designed to avoid redundancy in search area especially if the site is deemed unprofitable. This method is quite similar to Tabu Search (TS) with the POA-BA forbids the exact exploitation of previously visited solutions along with their corresponding neighbourhood. Patches are not allowed to intersect not just in the next generation but also in the current cycle. This reduces the number of patches materialise in the same peak (maximisation) or valley (minimisation) which ensures a thorough search of the problem landscape as bees are distributed around the scaled down area. The same benchmark problems as PG-BA were applied against this modified strategy to a reasonable success. Finally, the Bees Algorithm is revised to have the capability of locating all of the global optimum as well as the substantial local peaks in a single run. These multi-solutions of comparable fitness offers some alternatives for the decision makers to choose from. The patches are formed only if the bees are the fittest from different peaks by using a hill-valley mechanism in this so called Extended Bees Algorithm (EBA). This permits the maintenance of diversified solutions throughout the search process in addition to minimising the chances of getting trap. This version is proven beneficial when tested with numerous multimodal optimisation problems

Enhancing the bees algorithm using the traplining metaphor

This work aims to improve the performance of the Bees Algorithm (BA), particularly in terms of simplicity, accuracy, and convergence. Three improvements were made in this study as a result of bees’ traplining behaviour. The first improvement was the parameter reduction of the Bees Algorithm. This strategy recruits and assigns worker bees to exploit and explore all patches. Both searching processes are assigned using the Triangular Distribution Random Number Generator. The most promising patches have more workers and are subject to more exploitation than the less productive patches. This technique reduced the original parameters into two parameters. The results show that the Bi-BA is just as efficient as the basic BA, although it has fewer parameters. Following that, another improvement was proposed to increase the diversification performance of the Combinatorial Bees Algorithm (CBA). The technique employs a novel constructive heuristic that considers the distance and the turning angle of the bees’ flight. When foraging for honey, bees generally avoid making a sharp turn. By including this turning angle as the second consideration, it can control CBA’s initial solution diversity. Third, the CBA is strengthened to enable an intensification strategy that avoids falling into a local optima trap. The approach is based on the behaviour of bees when confronted with threats. They will keep away from re-visiting those flowers during the next bout for reasons like predators, rivals, or honey run out. The approach will remove temporarily threatened flowers from the whole tour, eliminating the sharp turn, and reintroduces them again to the habitual tour’s nearest edge. The technique could effectively achieve an equilibrium between exploration and exploitation mechanisms. The results show that the strategy is very competitive compared to other population-based nature-inspired algorithms. Finally, the enhanced Bees Algorithms are demonstrated on two real-world engineering problems, namely, Printed Circuit Board insertion sequencing and vehicles routing problem

Comparing Metaheuristic Algorithms for Sonet Network Design Problems

This paper considers two problems that arise in the design of optical telecommunication networks when a ring-based topology is adopted, namely the SONET Ring Assignment Problem and the Intraring Synchronous Optical Network Design Problem. We show that these two network topology problems correspond to graph partitioning problems with capacity constraints: the first is a vertex partitioning problem, while the latter is an edge partitioning problem. We consider solution methods for both problems, based on metaheuristic algorithms. We first describe variable objective functions that depend on the transition from one solution to a neighboring one, then we apply several diversification and intensification techniques including Path Relinking, eXploring Tabu Search and Scatter Search. Finally we propose a diversification method based on the use of multiple neighborhoods. A set of extensive computational results is used to compare the behaviour of the proposed methods and objective functions

Comparing metaheuristic algorithms for Sonet network design problems

This paper considers two problems that arise in the design of optical telecommunication networks when a ring-based topology is adopted, namely the SONET Ring Assignment Problem and the Intraring Synchronous Optical Network Design Problem. We show that these two network topology problems correspond to graph partitioning problems with capacity constraints: the first is a vertex partitioning problem, while the latter is an edge partitioning problem. We consider solution methods for both problems, based on metaheuristic algorithms. We first describe variable objective functions that depend on the transition from one solution to a neighboring one, then we apply several diversification and intensification techniques including Path Relinking, eXploring Tabu Search and Scatter Search. Finally we propose a diversification method based on the use of multiple neighborhoods. A set of extensive computational results is used to compare the behaviour of the proposed methods and objective functions