A study of the effects of clustering and local search on radio network design: evolutionary computation approaches

Eighth International Conference on Hybrid Intelligent Systems. Barcelona, 10-12 September 2008The goal of this paper is twofold. First, we want to make a study about how evolutionary computation techniques can efficiently solve the radio network design problem. For this goal we test several evolutionary computation techniques within the OPLINK experimental framework and compare them. Second, we propose a clustering approach and a 2-OPT in order to improve the results obtained by the evolutionary algorithms. Experiments carried out provide empirical evidence of how clustering-based techniques help in improving all algorithms tested. Extensive computational tests, including ones without clustering and 2-OPT, are performed with three evolutionary algorithms: genetic algorithms, memetic algorithms and chromosome appearance probability matrix algorithms.Publicad

Benchmarking a wide spectrum of metaheuristic techniques for the radio network design problem

The radio network design (RND) is an NP-hard optimization problem which consists of the maximization of the coverage of a given area while minimizing the base station deployment. Solving RND problems efficiently is relevant to many fields of application and has a direct impact in the engineering, telecommunication, scientific, and industrial areas. Numerous works can be found in the literature dealing with the RND problem, although they all suffer from the same shortfall: a noncomparable efficiency. Therefore, the aim of this paper is twofold: first, to offer a reliable RND comparison base reference in order to cover a wide algorithmic spectrum, and, second, to offer a comprehensible insight into accurate comparisons of efficiency, reliability, and swiftness of the different techniques applied to solve the RND problem. In order to achieve the first aim we propose a canonical RND problem formulation driven by two main directives: technology independence and a normalized comparison criterion. Following this, we have included an exhaustive behavior comparison between 14 different techniques. Finally, this paper indicates algorithmic trends and different patterns that can be observed through this analysis.Publicad

Diseño de redes de radio mediante la aplicación de algoritmos bioinspirados

Este trabajo, se centrará en el estudio de los resultados obtenidos con distintos algoritmos bioinspirados para el problema concreto del diseño de redes de comunicación para un escenario concreto. Con el desarrollo del presente proyecto, se tiene como objetivo resolver el problema RND (Radio Network Design), que trata de dar solución al diseño de redes de comunicación, y que se encuentra enmarcado dentro del terreno de las telecomunicaciones. Tal y como ya se explicó en el capítulo anterior del presente documento, este problema trata de conseguir dar cobertura a la mayor superficie posible de un terreno determinado, colocando estratégicamente el mínimo número posible de antenas para proporcionar dicha cobertura. Por lo tanto, este problema trata de obtener unas soluciones que consigan maximizar la cobertura proporcionada, minimizando el número de antenas empleadas para ello. Con el desarrollo de este proyecto, se pretende probar nuevas técnicas o modificaciones de otras existentes, para dar solución a este problema en un escenario concreto, con el objetivo de obtener unos resultados competitivos en referencia a los obtenidos en estudios anteriores.Ingeniería en Informátic

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Location aware advertisement insertion for mobile network video streams

Mobile phone networks are on the verge of a major breakthrough in terms of the services they offer. At the same time, active networks are being presented as the next step in the evolution of network architecture, with the aim of providing greater functionality within the network but retaining flexibility. At the same time, the 3G revolution seems to be floundering, due to the need to make a financial return on the huge investment tied up in the licences. This thesis seeks to provide a way forward, by investigating the implementation of a novel service that is the provision of video streaming across the mobile network with location dependent advertisement insertion. The work retains flexibility within the network architecture to enable additional services to be evolved and implemented with minimal modification to the nodes. The approach taken is to combine the traditional architecture with active functionality. As a result this thesis describes a novel service, the implementation of a short video service with location dependent advertisement insertion. This enables the provider to generate an income by transporting the service (it is possible for a third party to generate the content instead of the network provider) and by selling the advertisement space. This thesis investigates the implementation issues involved in providing the service and presents a protocol for the operation of it. The impact of this service on other users is also studied with the conclusion being that it does not adversely effect the quality of service of the voice traff ic within the network. In order to investigate the implementation of the protocol, a simulation model was constructed in OPNET [42]. This enabled the operation of the protocol to be tested under artificial conditions using fixed movements, to verify that it operated as specified. Then under more realistic conditions, so as to predict its effect on the other traffic in the network

Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem

Abstract. RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor networks. This problem consists in covering a certain geographical area by using the smallest number of radio antennas achieving the biggest cover rate. To date, several radio antenna models have been used: square coverage antennas, omnidirectional antennas that cover a circular area, etc. In this work we use omnidirectional antennas. On the other hand, RND is an NP-hard problem; therefore its solution by means of evolutionary algorithms is appropriate. In this work we study different evolutionary approaches to tackle this problem. PBIL (Population-Based Incremental Learning) is based on genetic algorithms and competitive learning (typical in neural networks). DE (Differential Evolution) is a very simple population-based stochastic function minimizer used in a wide range of optimization problems, including multi-objective optimization. SA (Simulated Annealing) is a classic trajectory descent optimization technique. Finally, CHC is a particular class of evolutionary algorithm which does not use mutation and relies instead on incest prevention and disruptive crossover. Due to the complexity of such a large analysis including so many techniques, we have used not only sequential algorithms, but also grid computing with BOINC in order to execute thousands of experiments in only several days using around 100 computers