Estratégias de escalonamento de workflows com tarefas paralelas e sequenciais em grades computacionais.

Abstract

The demand for high performance is a common problem in many scientific applications. In this sense, distributed processing environments such as cluster, grid computing and multi-cluster environments have been developed to provide support for the use of several resources simultaneously for the same application. Computationally intensive applications are structured as workflows and executed with the support of middleware to abstract the complexity of using such environments. In grid computing environments the execution of workflows containing sequential and parallel tasks, with good performance is a challenge due to the heterogeneity and dynamic behavior of the environment. In this sense, the scheduling of workflows on grid computing environments is essential. The task scheduling problem in its general form is NP-Complete, in this sense, the study concerning workflow scheduling in grid computing environments is fundamental to improve the performance of computationally intensive applications. The aim of this thesis is to propose strategies for scheduling workflows that exploit the following aspects: • Explore the possibility of performing single parallel tasks using multiple clusters; • Adaptation plans escalation in accordance with the submission of new workflows. Two strategies were developed: the first one is a strategy for static scheduling of workflows, which considers a dedicated environment to the execution of a workflow. The second one was developed to use in conjunction with the first one, in order to improve the response time of multiple workflows that can be submitted at different times. The proposed strategies were evaluated in a simulation environment. Key-words: multi-cluster, workflow scheduling;