A Performance Prediction Module for Workflow Scheduling

• Autores: Monge, David A.; Bělohradský, Jiří; García Garino, Carlos; Železný, Filip
• Año de publicación: 2011
• Idioma: inglés
• Tipo de recurso: documento de conferencia
• Materia: Ciencias Informáticas; Workflow; Scheduling; Performance Prediction; Nonparametric Regression
• Institución: Universidad Nacional de La Plata

Through the years, scientific applications have demanded more powerful and sophisticated computing environments and management techniques. Workflows facilitated the design and management of scientific applications. The complexity of to day's workflows demand a high amount of resources and mechanisms for provisioning them. The execution of scientific workflow applications is a complex task and depends on how the resources are assigned. Scheduling is the name given to the process that assigns computing resources to the tasks comprised in a workflow. This work presents a scheduling algorithm (PPSA) for workflows tightly coupled to a performance prediction module (PEM). A set of experiments was developed for measuring the performance of the algorithm using the information provided by the proposed performance module. The proposed algorithm is compared with an algorithm included in the well-known workflow middlewares Condor DAGMan and ASKALON.
Sociedad Argentina de Informática e Investigación Operativa