ESTG - Capítulos de livros
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- Parameter Analysis for Differential Evolution with Pareto Tournaments in a Multiobjective Frequency Assignment ProblemPublication . Maximiano, Marisa; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.This paper presents a multiobjective approach for the Frequency Assignment Problem (FAP) in a real-world GSM network. Indeed, nowadays in GSM systems, the FAP stills continues to be a critical task for the mobile communication operators. In this work we propose a new method to address the FAP by applying the Differential Evolution (DE) algorithm in its multiobjective optimization, using the concept of Pareto Tournaments (DEPT). We present the results obtained in the tuning process of the DEPT parameters. Two distinct real-world instances of the problem - being currently operating - were tested with DEPT algorithm. Therefore, with this multiobjective approach for the FAP we are contributing to a really important applicability.
- Multiple Description Coding for Multipath Video StreamingPublication . Correia, Pedro; Assunção, Pedro; Silva, VítorThis Chapter addresses robust video coding and adaptation of compressed streams in multipath communications environments, using Multiple Description Coding (MDC). A review of Multiple Description (MD) video coding is presented, covering different video coding approaches. Different path diversity topologies and MDC networking applications are described, including MD video adaptation schemes to operate at network edges, for robust video streaming. A multi-loop architecture for Advanced Video Coding (AVC) to prevent drift distortion accumulation is also described. A simulation study of MDC for AVC is presented to evaluate the coding efficiency, the effects of distortion propagation and streaming performance in lossy networks. These research findings extend the current state-of-the-art MDC methods by developing new networking capabilities in different application scenarios maintaining coding efficiency, and increasing error robustness, when subject to transmission losses.
- Video Transcoding TechniquesPublication . Moiron, Sandro; Ghanbari, Mohammed; Assunção, Pedro; Faria, SergioThis chapter addresses the most recent advances in video transcoding and processing architectures for multimedia content adaptation. The first section provides an overview of the state of the art, where video transcoding is described as a key solution to enable seamless interoperability across diverse multimedia communication systems and services. Then, a detailed analysis of relevant transcoding functions is presented, addressing their implementation, coding performance and computational complexity. The different processing architectures that can be used for video transcoding are also described, according to their respective functionalities and application scenarios. Other solutions capable of providing adaptation of coded video to heterogeneous environments, such as scalable video coding and multiple description video coding are also discussed and their main advantages and disadvantages are highlighted. A case study is also presented to illustrate the need and effectiveness of video transcoding in modern applications.
- The Radio Network Design Optimization ProblemPublication . Mendes, Silvio; Gómez-Pulido, Juan A.; Vega-Rodríguez, Miguel A.; Sánchez-Pérez, Juan M.; Sáez, Yago; Isasi, PedroThe fast growth and merging of communication infrastructures and services turned the planning and design of wireless networks into a very complex subject. The Radio Network Design (RND) is a NP-hard optimization problem which consists on the maximization of the coverage of a given area while minimizing the base station (BS) deployment. Solving such problems resourcefully is relevant for many fields of application and has direct impact in engineering, scientific and industrial areas. Its significance is growing due to cost dropping or profit increase allowance and can additionally be applied to several different business targets. Numerous works can be found in the literature dealing with the RND problem, although they all suffer from the same shortfall: a non-comparable efficiency. Therefore, the aim of this work is threefold: first, to offer a reliable RND benchmark reference covering a wide algorithmic spectrum, second, to offer a grand insight of accurately comparisons of efficiency, reliability and swiftness of the different employed algorithmic models and third, to disclose reproducibility details of the implemented models, including simulations of a hardware co-processing accelerator.
- Applying Scatter Search to the Location Areas ProblemPublication . Luz, Sónia Maria Almeida da; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.The Location Areas scheme is one of the most common strategies to solve the location management problem, which corresponds to the management of the mobile network configuration with the objective of minimizing the involved costs. This paper presents a new approach that uses a Scatter Search based algorithm applied to the Location Areas scheme as a cost optimization problem. With this work we pretend to analyze and set the main parameters of scatter search, using four distinct test networks and compare our results with those achieved by other authors. This is a new approach to this problem and the results obtained are very encouraging because they show that the proposed technique outperforms the existing methods in the literature.
- Solving the weighted ring edge-loading problem without demand splitting using a Hybrid Differential Evolution AlgorithmPublication . Bernardino, Anabela; Bernardino, Eugénia; Sanchez-Perez, Juan Manuel; Gomez-Pulido, Juan Antonio; Vega-Rodriguez, Miguel AngelIn the last few years we have seen a significant growth in Synchronous Optical Network (SONET) deployments in telecommunication service providers. With growth of data traffic, network operators seek network-engineering tools to extract the maximum benefits out of the existing infrastructure. This has suggested a number of new optimization problems, most of them in the field of combinatorial optimization. We address here the Weighted Ring Edge-Loading Problem (WRELP). The WRELP is an important optimization problem arising in a popular ring topology for communication networks - given a set of nodes connected along a bi-directional SONET ring, the objective is to minimize the maximum load on the edges (pairwise) of a ring. Our procedure includes some original features, including the application of Hybrid Differential Evolution. We also perform comparisons with standard Differential Evolution, Genetic Algorithm and Tabu Search.
- Knowledge Extraction with Non-Negative Matrix Factorization for Text ClassificationPublication . Silva, Catarina; Ribeiro, BernardeteText classification has received increasing interest over the past decades for its wide range of applications driven by the ubiquity of textual information. The high dimensionality of those applications led to pervasive use of dimensionality reduction methods, often black-box feature extraction non-linear techniques. We show how Non-Negative Matrix Factorization (NMF), an algorithm able to learn a parts-based representation of data by imposing non-negativity constraints, can be used to represent and extract knowledge from a text classification problem. The resulting reduced set of features is tested with kernel-based machines on Reuters-21578 benchmark showing the method's performance competitiveness.
- A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment ProblemPublication . Bernardino, Eugénia; Bernardino, Anabela; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelThe field of communication networks has witnessed tremendous growth in recent years resulting in a large variety of combinatorial optimization problems in the design and in the management of communication networks. One of these problems is the terminal assignment problem. The task here is to assign a given set of terminals to a given set of concentrators. In this paper, we propose a Hybrid Differential Evolution Algorithm to solve the terminal assignment problem. We compare our results with the results obtained by the classical Genetic Algorithm and the Tabu Search Algorithm, widely used in literature.
- Design of Radio-Frequency Integrated CMOS Discrete Tuning Varactors Using the Particle Swarm Optimization AlgorithmPublication . Pires, E. J. Solteiro; Mendes, Luís; Oliveira, P. B. de Moura; Machado, J. A. Tenreiro; Vaz, João C.; Rosário, Maria J.This paper presents an automated design procedure of radio- frequency integrated CMOS discrete tuning varactors (RFDTVs). This new method use the maximin and the particle swarm optimization (PSO) algorithms to promote well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. The fitness function used in the search tool is proportional to the RFDTV quality factor. The outcome of the automated design method comprises a set of RFDTV circuits, all having the same maximum performance. Each solution, which corresponds to one RFDTV circuit, is defined by the number of cells and by the circuit components values. This approach allows the designer to choose among several possible circuits the one that is easier to implement in a given CMOS process. To validate the effectiveness of the synthesis procedure proposed in this paper (PSO-method) comparisons with a design method based on genetic algorithms (GA-method) are presented. A 0.18 μm CMOS radio-frequency binary-weighted differential switched capacitor array (RFDSCA) was designed and implemented (the RFDSCA is one of the possible topologies of the RFDTVs). The results show that both design methods are in very good agreement. However, the PSO technique outperforms the GA-method in the design procedure run time taken to accomplish the same performance results.
- Improving Visualization, Scalability and Performance of Multiclass Problems with SVM Manifold LearningPublication . Silva, Catarina; Bernardete RibeiroWe propose a learning framework to address multiclass challenges, namely visualization, scalability and performance. We focus on supervised problems by presenting an approach that uses prior information about training labels, manifold learning and support vector machines (SVMs). We employ manifold learning as a feature reduction step, nonlinearly embedding data in a low dimensional space using Isomap (Isometric Mapping), enhancing geometric characteristics and preserving the geodesic distance within the manifold. Structured SVMs are used in a multiclass setting with benefits for final multiclass classification in this reduced space. Results on a text classification toy example and on ISOLET, an isolated letter speech recognition problem, demonstrate the remarkable visualization capabilities of the method for multiclass problems in the severely reduced space, whilst improving SVMs baseline performance.