DocumentCode
3509536
Title
An Architecture for Guaranteeing Real-Time Databases Available Ceaselessly
Author
Xiao, Ying-yuan
Author_Institution
Sch. of Comput. Sci. & Technol., Tianjin Univ. of Technol., Tianjin
fYear
2008
fDate
21-23 Oct. 2008
Firstpage
172
Lastpage
177
Abstract
Real-time databases are widely applied in time-critical applications, such as autopilot systems, robot navigation, real-time monitoring, programmed stock trading, etc. These applications usually require real-time databases can provide 7times24times60times60s´ ceaseless service weekly. However, real-time databases cannot completely avoid all kinds of failures. The traditional recovery-processing scheme cannot already satisfy the requirement for the above applications. In this paper, we present a fault tolerant architecture based on self-perceptive, self-diagnosing and self-adaptive recovery mechanisms. This architecture can prevent or delay failures effectively. On the basis of this architecture, we propose a novel prediction recovery scheme. The prediction recovery scheme allows the execution of transactions during recovery by providing predictive values of damaged data items to these transactions that need immediate access to those data items.
Keywords
database management systems; fault diagnosis; fault tolerant computing; real-time systems; system recovery; transaction processing; fault tolerant architecture; prediction recovery scheme; real-time database; recovery-processing scheme; self-adaptive recovery mechanism; self-diagnosing recovery mechanism; transaction processing; Application software; Computer crashes; Condition monitoring; Conferences; Delay effects; Distributed computing; Distributed databases; Navigation; Real time systems; Transaction databases; fault tolerant architecture; prediction recovery scheme; real-time database;
fLanguage
English
Publisher
ieee
Conference_Titel
Future Trends of Distributed Computing Systems, 2008. FTDCS '08. 12th IEEE International Workshop on
Conference_Location
Kunming
ISSN
1071-0485
Print_ISBN
978-0-7695-3377-3
Type
conf
DOI
10.1109/FTDCS.2008.12
Filename
4683132
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