Full text
![]()
|
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (412kB) |
Capelastegui de la Concha, Pedro and Navas Baltasar, Alvaro and Huertas Ferrer, Francisco and Garcia Carmona, Rodrigo and Dueñas López, Juan Carlos (2013). An online failure prediction system for private IaaS platforms. In: "2nd International Workshop on Dependability Issues in Cloud Computing (DISCCO 2013)", 30/09/2013, Braga, Portugal. https://doi.org/10.1145/2506155.2506159.
Title: | An online failure prediction system for private IaaS platforms |
---|---|
Author/s: |
|
Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 2nd International Workshop on Dependability Issues in Cloud Computing (DISCCO 2013) |
Event Dates: | 30/09/2013 |
Event Location: | Braga, Portugal |
Title of Book: | 2nd International Workshop on Dependability Issues in Cloud Computing (DISCCO 2013) |
Date: | 2013 |
Subjects: | |
Freetext Keywords: | OFP, cloud, IaaS, reliability |
Faculty: | E.T.S.I. Telecomunicación (UPM) |
Department: | Ingeniería de Sistemas Telemáticos |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
![]()
|
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (412kB) |
The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines di_erent types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments.
Item ID: | 25767 |
---|---|
DC Identifier: | https://oa.upm.es/25767/ |
OAI Identifier: | oai:oa.upm.es:25767 |
DOI: | 10.1145/2506155.2506159 |
Deposited by: | Memoria Investigacion |
Deposited on: | 10 May 2014 12:17 |
Last Modified: | 22 Sep 2014 11:38 |