216 resultados para MESTRADO EM SISTEMAS DE COMUNICA


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Cloud computing can be defined as a distributed computational model by through resources (hardware, storage, development platforms and communication) are shared, as paid services accessible with minimal management effort and interaction. A great benefit of this model is to enable the use of various providers (e.g a multi-cloud architecture) to compose a set of services in order to obtain an optimal configuration for performance and cost. However, the multi-cloud use is precluded by the problem of cloud lock-in. The cloud lock-in is the dependency between an application and a cloud platform. It is commonly addressed by three strategies: (i) use of intermediate layer that stands to consumers of cloud services and the provider, (ii) use of standardized interfaces to access the cloud, or (iii) use of models with open specifications. This paper outlines an approach to evaluate these strategies. This approach was performed and it was found that despite the advances made by these strategies, none of them actually solves the problem of lock-in cloud. In this sense, this work proposes the use of Semantic Web to avoid cloud lock-in, where RDF models are used to specify the features of a cloud, which are managed by SPARQL queries. In this direction, this work: (i) presents an evaluation model that quantifies the problem of cloud lock-in, (ii) evaluates the cloud lock-in from three multi-cloud solutions and three cloud platforms, (iii) proposes using RDF and SPARQL on management of cloud resources, (iv) presents the cloud Query Manager (CQM), an SPARQL server that implements the proposal, and (v) comparing three multi-cloud solutions in relation to CQM on the response time and the effectiveness in the resolution of cloud lock-in.

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The real-time embedded systems design requires precise control of the passage of time in the computation performed by the modules and communication between them. Generally, these systems consist of several modules, each designed for a specific task and restricted communication with other modules in order to obtain the required timing. This strategy, called federated architecture, is already becoming unviable in front of the current demands of cost, required performance and quality of embedded system. To address this problem, it has been proposed the use of integrated architectures that consist of one or few circuits performing multiple tasks in parallel in a more efficient manner and with reduced costs. However, one has to ensure that the integrated architecture has temporal composability, ie the ability to design each task temporally isolated from the others in order to maintain the individual characteristics of each task. The Precision Timed Machines are an integrated architecture approach that makes use of multithreaded processors to ensure temporal composability. Thus, this work presents the implementation of a Precision Machine Timed named Hivek-RT. This processor which is a VLIW supporting Simultaneous Multithreading is capable of efficiently execute real-time tasks when compared to a traditional processor. In addition to the efficient implementation, the proposed architecture facilitates the implementation real-time tasks from a programming point of view.

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Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

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Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

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Component-based Software Engineering (CBSE) and Service-Oriented Architecture (SOA) became popular ways to develop software over the last years. During the life-cycle of a software system, several components and services can be developed, evolved and replaced. In production environments, the replacement of core components, such as databases, is often a risky and delicate operation, where several factors and stakeholders should be considered. Service Level Agreement (SLA), according to ITILv3’s official glossary, is “an agreement between an IT service provider and a customer. The agreement consists on a set of measurable constraints that a service provider must guarantee to its customers.”. In practical terms, SLA is a document that a service provider delivers to its consumers with minimum quality of service (QoS) metrics.This work is intended to assesses and improve the use of SLAs to guide the transitioning process of databases on production environments. In particular, in this work we propose SLA-Based Guidelines/Process to support migrations from a relational database management system (RDBMS) to a NoSQL one. Our study is validated by case studies.

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Multi-objective problems may have many optimal solutions, which together form the Pareto optimal set. A class of heuristic algorithms for those problems, in this work called optimizers, produces approximations of this optimal set. The approximation set kept by the optmizer may be limited or unlimited. The benefit of using an unlimited archive is to guarantee that all the nondominated solutions generated in the process will be saved. However, due to the large number of solutions that can be generated, to keep an archive and compare frequently new solutions to the stored ones may demand a high computational cost. The alternative is to use a limited archive. The problem that emerges from this situation is the need of discarding nondominated solutions when the archive is full. Some techniques were proposed to handle this problem, but investigations show that none of them can surely prevent the deterioration of the archives. This work investigates a technique to be used together with the previously proposed ideas in the literature to deal with limited archives. The technique consists on keeping discarded solutions in a secondary archive, and periodically recycle these solutions, bringing them back to the optimization. Three methods of recycling are presented. In order to verify if these ideas are capable to improve the archive content during the optimization, they were implemented together with other techniques from the literature. An computational experiment with NSGA-II, SPEA2, PAES, MOEA/D and NSGA-III algorithms, applied to many classes of problems is presented. The potential and the difficulties of the proposed techniques are evaluated based on statistical tests.

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Multi-objective problems may have many optimal solutions, which together form the Pareto optimal set. A class of heuristic algorithms for those problems, in this work called optimizers, produces approximations of this optimal set. The approximation set kept by the optmizer may be limited or unlimited. The benefit of using an unlimited archive is to guarantee that all the nondominated solutions generated in the process will be saved. However, due to the large number of solutions that can be generated, to keep an archive and compare frequently new solutions to the stored ones may demand a high computational cost. The alternative is to use a limited archive. The problem that emerges from this situation is the need of discarding nondominated solutions when the archive is full. Some techniques were proposed to handle this problem, but investigations show that none of them can surely prevent the deterioration of the archives. This work investigates a technique to be used together with the previously proposed ideas in the literature to deal with limited archives. The technique consists on keeping discarded solutions in a secondary archive, and periodically recycle these solutions, bringing them back to the optimization. Three methods of recycling are presented. In order to verify if these ideas are capable to improve the archive content during the optimization, they were implemented together with other techniques from the literature. An computational experiment with NSGA-II, SPEA2, PAES, MOEA/D and NSGA-III algorithms, applied to many classes of problems is presented. The potential and the difficulties of the proposed techniques are evaluated based on statistical tests.

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Given the growing demand for the development of mobile applications, driven by use increasingly common in smartphones and tablets grew in society the need for remote data access in full in the use of mobile application without connectivity environments where there is no provision network access at all times. Given this reality, this work proposes a framework that present main functions are the provision of a persistence mechanism, replication and data synchronization, contemplating the creation, deletion, update and display persisted or requested data, even though the mobile device without connectivity with the network. From the point of view of the architecture and programming practices, it reflected in defining strategies for the main functions of the framework are met. Through a controlled study was to validate the solution proposal, being found as the gains in reducing the number of lines code and the amount of time required to perform the development of an application without there being significant increase for the operations.

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Given the growing demand for the development of mobile applications, driven by use increasingly common in smartphones and tablets grew in society the need for remote data access in full in the use of mobile application without connectivity environments where there is no provision network access at all times. Given this reality, this work proposes a framework that present main functions are the provision of a persistence mechanism, replication and data synchronization, contemplating the creation, deletion, update and display persisted or requested data, even though the mobile device without connectivity with the network. From the point of view of the architecture and programming practices, it reflected in defining strategies for the main functions of the framework are met. Through a controlled study was to validate the solution proposal, being found as the gains in reducing the number of lines code and the amount of time required to perform the development of an application without there being significant increase for the operations.

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The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.

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The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.

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Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.

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Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.

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The Traveling Salesman with Multiple Ridesharing (TSP-MR) is a type of the Capacitated Traveling Salesman, which presents the possibility of sharing seats with passengers taking advantage of the paths the salesman travels through his cycle. The salesman shares the cost of a path with the boarded passengers. This model can portray a real situation in which, for example, drivers are willing to share parts of a trip with tourists that wish to move between two locations visited by the driver’s route, accepting to share the vehicle with other individuals visiting other locations within the cycle. This work proposes a mathematical formulation for the problem, and an exact and metaheuristics algorithms for its solution, comparing them.

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The Traveling Salesman with Multiple Ridesharing (TSP-MR) is a type of the Capacitated Traveling Salesman, which presents the possibility of sharing seats with passengers taking advantage of the paths the salesman travels through his cycle. The salesman shares the cost of a path with the boarded passengers. This model can portray a real situation in which, for example, drivers are willing to share parts of a trip with tourists that wish to move between two locations visited by the driver’s route, accepting to share the vehicle with other individuals visiting other locations within the cycle. This work proposes a mathematical formulation for the problem, and an exact and metaheuristics algorithms for its solution, comparing them.