Programa de Pós-graduação em Ciência da Computação em Rede
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Navegando Programa de Pós-graduação em Ciência da Computação em Rede por Por Orientador "Costa, Fábio Moreira"
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Item Programação de espaços inteligentes utilizando modelos em tempo de execução(Universidade Federal de Goiás, 2017-04-04) Freitas, Leandro Alexandre; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Silva, Francisco José da Silva e; Ueyama, Jó; Ferreira, Ronaldo Alves; Soares, Fabrízzio Alphonsus Alves de Melo NunesThe growth and popularization of wireless connectivity and of mobile devices has allowed the development of smart spaces that were previously only envisaged in the approach proposed by Mark Weiser. These smart spaces are composed of many computational resources, such as devices, services and applications, along with users, who must be able to associate with these features. However, programming these environments is a challenging task, since smart spaces have a dynamic nature, resources are heterogeneous, and it is necessary that interactions between users and devices are coordinated with one another. In this work, we present a new approach for smart spaces programming using Models@RunTime. In this regard, we propose a high level modeling language, called Smart Spaces Modeling Language (2SML), in which the user is able to model the smart space with all elements that can be part of it. Such models are developed by the users, interpreted and effected in the physical space by a model execution engine, called Smart Space Virtual Machine (2SVM), whose development is part of this work.Item Implantação eficiente de múltiplas coreografias de serviços em nuvens híbridas(Universidade Federal de Goiás, 2017-04-06) Gomes, Raphael de Aquino; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Rocha, Ricardo Couto Antunes da; Schulze, Bruno Richard; Cordeiro, Daniel de Angelis; Cáceres, Edson NorbertoThis thesis proposes a model-based approach to abstracting, simplifying, and automating cloud resource management decisions to deploy a set of service choreographies subject to non-functional constraints. Given a high-level description of service choreographies and related constraints, the approach autonomously performs resource estimation, selection, and allocation in a hybrid cloud environment with multiple cloud providers whilst decreases resource utilization costs and inter-services communication overhead. The main motivation for this work is because service choreographies are widely used for the development of solutions with complex needs, with service sharing among them. This scenario turns resource management a challenging task, mainly due to the different roles that a service assumes, the interference among constraints, and a large number of available resource types. This thesis also proposes an architecture that extends the approach with strategies to dynamic resource management to face constraint violations. This architecture was partially implemented in a prototype that was used in the proposed approach evaluation.Item Seleção de serviços sensível à QoS e à capacidade para implantação eficiente de múltiplas coreografias de serviços(Universidade Federal de Goiás, 2018-11-23) Lima, Júnio César de; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Rocha, Ricardo Couto Antunes da; Rosa, Nelson Souto; Madeira, Edmundo Roberto Mauro; Longo, Humberto JoséChoreographies are an approach for service composition in which coordination is performed in a decentralized way. To deploy a choreography, a set of services must be selected to perform the functionalities required in its specification, including ensuring its QoS requirements. However, existing approaches for QoS-aware service selection fail to explicitly consider service sharing, as they deal with each choreography in isolation. By dealing with a single choreography at a time, the service selection process may become less feasible in real scenarios, in which several choreographies, competing for the same set of services, must be deployed together. In this case, a given service that suits a role in more than one choreography may be shared. Unsupervised service sharing, however, may degrade the overall QoS provided for the choreographies, as the maximum capacity of the shared servicesmay be exceeded. In addition, such approaches tend to select services with higher QoS than necessary, leading to waste of resources. This thesis proposes an approach for QoS- and capacity-aware service selection for the combined deployment of multiple choreographies. This approach ensures the satisfaction of QoS requirements, even in the face of possible service sharing. To this end, we propose a model for the combined representation of multiple choreographies. This model is used as input for the service selection, which is solved by seeking a matching between of the choreographies roles and the candidate services to minimize the costs of the selected services in terms of resource usage. For this, a utility function is proposed to evaluate the QoS of the services, along with the extension of the matching algorithm. The thesis presents an architecture that combines all the elements of the proposed approach. A prototype implementation of the architecture was developed to enable its evaluation. The results of the evaluation indicate superior effectiveness and performance of the proposed approach as compared to related work.Item Efficient processing of multiway spatial join queries in distributed systems(Universidade Federal de Goiás, 2017-11-29) Oliveira, Thiago Borges de; Foulds, Leslie Richard; http://lattes.cnpq.br/3737395828552021; Rodrigues, Vagner José do Sacramento; http://lattes.cnpq.br/4148896613580056; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Foulds, Leslie Richard; Rodrigues, Vagner José do Sacramento; Braghetto, Kelly Rosa; Meneses, Cláudio Nogueira deMultiway spatial join is an important type of query in spatial data processing, and its efficient execution is a requirement to move spatial data analysis to scalable platforms as has already happened with relational and unstructured data. In this thesis, we provide a set of comprehensive models and methods to efficiently execute multiway spatial join queries in distributed systems. We introduce a cost-based optimizer that is able to select a good execution plan for processing such queries in distributed systems taking into account: the partitioning of data based on the spatial attributes of datasets; the intra-operator level of parallelism, which enables high scalability; and the economy of cluster resources by appropriately scheduling the queries before execution. We propose a cost model based on relevant metadata about the spatial datasets and the data distribution, which identifies the pattern of costs incurred when processing a query in this environment. We formalized the distributed multiway spatial join plan scheduling problem as a bi-objective linear integer model, considering the minimization of both the makespan and the communication cost as objectives. Three methods are proposed to compute schedules based on this model that significantly reduce the resource consumption required to process a query. Although targeting multiway spatial join query scheduling, these methods can be applied to other kinds of problems in distributed systems, notably problems that require both the alignment of data partitions and the assignment of jobs to machines. Additionally, we propose a method to control the usage of resources and increase system throughput in the presence of constraints on the network or processing capacity. The proposed cost-based optimizer was able to select good execution plans for all queries in our experiments, using public datasets with a significant range of sizes and complex spatial objects. We also present an execution engine that is capable of performing the queries with near-linear scalability with respect to execution time.