Fault Prediction: A Dynamic System-inspired Approach

• Grant number: 09/04645-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2009
• End date: February 28, 2011
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Rodrigo Fernandes de Mello
• Grantee: Cássio Martini Martins Pereira
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The technological development has allowed the reduction of costs involved in purchasing personal and high-end computers. Such resources started composing large scale as well as heterogeneous enviroments. Those enviroments have a high probability to experience faults, due to the number and heterogeneity of hardware and software resources. In order to reduce the resource downtime, several researchers have been conducted aiming at detecting faults and failures in such environments, pointing out such perturbations to system administrators. However, recent researches have been addressing the fault prediction by analysing information obtained through resource monitoring. Those researches are limited to forecast future events based on short-term memories. Such limitations motivated this work which proposes the study and application of dynamical system tools to analyze the long-term behavior of time series as a way to model and predict faults. Such series are unfolded and regressed in order to better observe tendencies, which support fault predictions and, therefore, the failure avoidance.

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

PEREIRA, CASSIO M. M.; DE MELLO, RODRIGO F.. LEARNING PROCESS BEHAVIOR FOR FAULT DETECTION. International Journal on Artificial Intelligence Tools, v. 20, n. 5, p. 969-980, OCT 2011. (09/04645-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

PEREIRA, Cássio Martini Martins. Fault detection an approach based on process behavior. 2011. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.