Submitted by Nadir Basilio (nadirsb@uninove.br) on 2016-06-01T14:36:20Z No. of bitstreams: 1 Jose Luiz Rodrigues Junior.pdf: 1816384 bytes, checksum: f83b0cfa9558fadd55f06d3f851584a9 (MD5) / Made available in DSpace on 2016-06-01T14:36:20Z (GMT). No. of bitstreams: 1 Jose Luiz Rodrigues Junior.pdf: 1816384 bytes, checksum: f83b0cfa9558fadd55f06d3f851584a9 (MD5) Previous issue date: 2015-06-17 / In current data centers, processing routines are scheduled to perform in a given period of time and, in case of delay, make it impossible to conduct the activities of everyday life of the various sectors of the company. Even with modern servers, due to the large volume of data to be processed, it is possible that certain computers are overloaded causing a drop in performance, a longer time to implement and consequently delays in the delivery of results. In this case, alternative scenarios can be created to sequence the tasks again. This work aimed to apply the multi-criteria decision analysis method on the results of the simulation of alternative scenarios for sequencing tasks on computers in a datacenter, in order to overload the resolution of problems. To achieve this purpose have been developed simulation models of task sequencing scenarios and replacement of computer overloaded. The analysis of simulation results was made based on three criteria, namely the Total Processing Time (makespan), the Total delay time, and the number of Delayed Tasks. Subsequently, the results were submitted to analysis method of AHP multicriteria decision (Analitycal Hierarchy Process), allowing you to choose the best setting according to established criteria. It was concluded that the modeling and computer simulation, combined with multi-criteria decision analysis method, can aid in decision making, as it enables sequencing to identify the best solution possible alternative scenarios in front of a computer overload situations. / Nos atuais Datacenters, as rotinas de processamento são programadas para executar em determinado período de tempo e, em caso de atraso, impossibilitar a condução das atividades do dia a dia dos diversos setores da empresa. Mesmo com os modernos servidores, devido ao grande volume de dados para serem processados, é possível que determinados computadores sejam sobrecarregados provocando uma queda em seu desempenho, um tempo maior para a execução e, consequentemente, atrasos na entrega dos resultados. Nesse caso, cenários alternativos podem ser criados para sequenciar novamente as tarefas. Assim, este trabalho teve por objetivo aplicar o método de análise de decisão multicritério nos resultados da simulação de cenários alternativos para o sequenciamento de tarefas em computadores de um Datacenter, visando a resolução para problemas de sobrecarga. Para atingir esse propósito, foram desenvolvidos modelos de simulação de cenários de sequenciamento de tarefas e substituição do computador com sobrecarga. A análise dos resultados da simulação foi realizada considerando três critérios, a saber: o Tempo Total de Processamento (makespan), o Tempo Total de Atraso, e o Número de Tarefas Atrasadas. Posteriormente, os resultados foram submetidos ao método de análise de decisão multicritério AHP (Analitycal Hierarchy Process), permitindo escolher o melhor cenário segundo os critérios estabelecidos. Concluiu-se que a modelagem e simulação computacional, aliada ao método de análise de decisão multicritério, pode auxiliar na tomada de decisão, uma vez que possibilita identificar a melhor solução de sequenciamento em cenários alternativos possíveis diante de situações de sobrecarga de um computador.

My work is aiming at establishing the bases of a semiotics of motion, in order to facilitate the programing of complex robotics systems. The objective is to build a symbolic model of the action, based on the analysis of the numerical functions that drive the motion (control and planning). The methodology comes from the well-known robotics concepts: motion-planning algorithms, control of redundant systems and task-function approach. The originality of the work is to consider the "task" as the unifying concept both to describe the motion and to control its execution. The document is organized in two parts. In the first part, the task-function control framework is extended to cover all the possible modalities of the robot. The objective is to absorb from the lowest-possible functional level the maximum of uncertainty factors. It is then not any more necessary to model these factors at the higher functional levels. This sensorimotor layer is then used as a basic action "vocabulary" that enables the system to be controlled with a higher-level interface. In the second part, this action vocabulary is used to provide a dedicated robotics programing language, to build motion-planning methods and to describe an observed movement. The proposed methods are generic and can be applied to a various systems, from robotics (redundant robots) to computer animation (virtual avatars). Nonetheless, the work is more specifically dedicated to humanoid robotics. Without forgetting other possible outlets, humanoid robotics provides a tangible applicative and experimental framework. It also leads toward the natural human motion, as presented in the end of the document.