DSpace Coleção:
http://www.repositorio.ufc.br/handle/riufc/384
Sun, 20 Oct 2019 21:48:14 GMT2019-10-20T21:48:14ZMathematical programming approaches for NP-Hard constrained shortest path problems
http://www.repositorio.ufc.br/handle/riufc/46642
Título: Mathematical programming approaches for NP-Hard constrained shortest path problems
Autor(es): Saraiva, Rommel Dias
Abstract: In this work, we study two NP-Hard routing problems: the shortest path with negative cycles (SPNC) and the constrained shortest path tour problem (CSPTP). For the SPNC, we propose three exact approaches based on mathematical programming: a compact mixed integer linear programming model, a specialized branch-and-bound algorithm, and a cutting-plane method. We perform numerical experiments comprising both randomly generated and benchmark instances from the literature. The computational tests show that the proposed approaches stand out from state-of-the-art mathematical programming techniques. Moreover, we discuss the linear relaxations of models present it the literature. Concerning the CSPTP, we show two compact models for the problem: a pure integer linear programming model, which we call dummy node-based model; and a mixed integer linear programming one, which we call frontier node-based model. For the latter, we show valid inequalities and propose deterministic and non-deterministic Lagrangian heuristics. Experiments performed on both randomly generated and benchmark instances from the literature validate and attest the effectiveness of our contributions, which achieve the optimal solution in the vast majority of cases. We show that the dummy node and the frontier node-based models alternate better results depending on the characteristics of each instance. The efficiency over specialized branch-and-bound algorithms from the literature is also proven through experiments, as well as the potentialities behind the Lagrangian heuristics, which find the optimal solution for a large number of instances.Tue, 01 Jan 2019 00:00:00 GMThttp://www.repositorio.ufc.br/handle/riufc/466422019-01-01T00:00:00ZSistema de apoio a decisão para implantar uma aplicação baseada em microsserviços em um ambiente multi-cloud
http://www.repositorio.ufc.br/handle/riufc/46144
Título: Sistema de apoio a decisão para implantar uma aplicação baseada em microsserviços em um ambiente multi-cloud
Autor(es): Carvalho, Juliana Oliveira de
Abstract: Cloud computing has become a trendy model of service delivery, bringing various benefits. However, to apply the cloud model in specific scenarios, some challenges must be overcome. One of these problems is to deploy and run applications in various providers, and each one comprises several services with similar functionalities and different capabilities. Thus, dealing with issues of application distributions in multiple providers is a complex task for a software architect, since the components of an application have different characteristics. Solutions have been proposed to face this problem, but most of them focus on service providers. Therefore, we propose a cost-effective decision-making system to deploy a distributed application across multiple cloud providers. We consider in this work applications based on microservices, for offering greater flexibility. Thus, the proposed solution select providers that best meet the microservices and software architect requisites, in a manner that the microservices can be deployed in many providers. We propose three selection models for the system to serve a variety of scenarios. To reach the objectives, we also offer a definition, a classification and taxonomies for the management of resources in multiple providers from the perspective of a software architect, and a definition of microservices in the context of multi-cloud. Further, we propose PacificClouds, an architecture for managing the deployment and execution of applications based on microservices distributed multi-cloud. In the end, we accomplished a comparative analysis of the three proposed models, which one shows the feasibility concerning the performance of the solutions applied in each of the models.Tue, 01 Jan 2019 00:00:00 GMThttp://www.repositorio.ufc.br/handle/riufc/461442019-01-01T00:00:00ZUma técnica de decomposição de domínios a priori para geração automática de malhas tetraédricas em paralelo
http://www.repositorio.ufc.br/handle/riufc/45591
Título: Uma técnica de decomposição de domínios a priori para geração automática de malhas tetraédricas em paralelo
Autor(es): Teixeira, Daniel Nascimento
Abstract: This work proposes a fully automated technique for domain decomposition to generate meshes using parallel computers with distributed memory. This technique relies on a partitioning structure that uses axis-aligned planes to decompose the domain. These decomposing planes are determined by a binary partitioning structure based on a refined quadtree (in two-dimensional case) or octree (in three-dimensional case) that is built to estimate the amount of work necessary to generate the whole mesh. Thus, the amount of work in each subdomain is approximately the same. The level of refinement of the quadtree or octree is used to guide the creation of each subdomain’s interface, defined by its inter-cell discretization. The interface mesh generation
is performed a priori, i.e., every subdomain has its interface mesh fully created and improved before the internal mesh generation phase. This technique generates new domains completely independent from one another and allows to abstract the mesh generation technique applied to the subdomains, which can combine, for example, Delaunay and Advancing Front Techniques, among others. Also, the load estimation technique produces results that accurately represent the number of elements to be generated in each subdomain, leading to an adequate prediction of execution time and a well-balanced algorithm, a desirable feature in parallel processing that is usually difficult to achieve. The meshes generated with the parallel technique have the same quality as those generated serially, within acceptable limits, which is desired from parallel approaches.Tue, 01 Jan 2019 00:00:00 GMThttp://www.repositorio.ufc.br/handle/riufc/455912019-01-01T00:00:00ZSmart Shadow - Predictive computing resources allocation for smart devices in the mist computing environment
http://www.repositorio.ufc.br/handle/riufc/45242
Título: Smart Shadow - Predictive computing resources allocation for smart devices in the mist computing environment
Autor(es): Vasconcelos, Danilo Reis de
Abstract: The Internet of Things (IoT) is a technological revolution that has generated new opportunities in academia and industry. In this context, IoT enables the emergence of several new ecosystems and computing environments. One of these new environments that, in the view of some authors, is considered of high importance in the context of the IoT devices is Fog and Mist Computing (FMC). FMC uses computational resources located at the edge of the network, reducing the latency and bandwidth problems, when compared to the use of Cloud computing platforms focused on IoT applications, also called Cloud of Things (CoT). Both infrastructures Fog and Mist computing are located on the edge of the network, however, the Fog computing processing usually occurs at the gateway layer that connects the IoT devices with the Internet. On the other hand, Mist computing, although it is a subset of Fog computing, concentrates its processing in the direct neighborhood of the device. The FMC environment offers new opportunities and benefits, however, due to the considerable dynamism of the topology and heterogeneity of devices, new challenges also arise. This thesis focuses on the problem of how to handle with this dynamism considering the issue of predictive discovery of computational resources in this environment and, thus, proposing a predictive model based on collective knowledge of previous experiences of resource allocations used by IoT devices in this ecosystem. In the proposal, the problem is subdivided into three distinct sub-problems, as follows. The first is how to evaluate from the client device perspective if it is interesting to use the infrastructure of the Fog/Mist/Cloud computing. Subsequently, once the answer is positive for Fog or Mist computing, the work seeks to find mechanisms on how to maintain data in this highly dynamic environment of the network topology. To address this issue, the work proposes a bio-inspired self-adaptive hierarchy structure of devices that use epidemic models to address this problem. Finally, the work presents a prediction algorithm of resources based on collaborative filters combined with an estimator of temporal availability of the devices that are part of the FMC environment. The evaluation is done with simulation using the Contiki operating system and the simulator Cooja. The results suggest the effectiveness of the proposal, even in cases where the FMC environment is composed of few devices that follow a pattern of permanence behavior within the network.Mon, 01 Jan 2018 00:00:00 GMThttp://www.repositorio.ufc.br/handle/riufc/452422018-01-01T00:00:00Z