DocumentCode :
1218032
Title :
Intelligent Monitoring for Adaptation in Grid Applications
Author :
Reed, Daniel A. ; Mendes, Celso L.
Author_Institution :
Renaissance Comput. Inst., Univ. of North Carolina, Chapel Hill, NC, USA
Volume :
93
Issue :
2
fYear :
2005
Firstpage :
426
Lastpage :
435
Abstract :
Grid applications access distributed, and often shared, resources. One consequence of this resource sharing is that measured application performance can vary widely and in unexpected ways. Determining the causes of poor performance, due to either anomalous application behavior or contention for shared resource use, and adapting to changing circumstances are critical to creation of robust Grid applications. Performance contracts and real-time adaptive control are two mechanisms to realize soft performance guarantees in Grid environments. Performance contracts formalize the relationship between application performance needs and resource capabilities. During execution, contract monitors use performance data to verify that expectations are met. When the contracted specifications are not satisfied, the system can choose to either adapt the application to available resources or reschedule the application on a new set of resources that can satisfy the original contract specifications. We describe an infrastructure for Grid application contract development and monitoring. This infrastructure, based on the Autopilot toolkit, provides flexible and scalable tools to assess both application and system behavior.
Keywords :
adaptive control; grid computing; middleware; parallel processing; Autopilot toolkit; contract development; distributed computing; grid application contract development; intelligent monitoring; parallel processing; performance contracts; real time adaptive control; resource sharing; Adaptive control; Contracts; Distributed computing; Distributed control; Extraterrestrial measurements; Large Hadron Collider; Monitoring; Parallel processing; Resource management; Robustness; Adaptive control; distributed computing; monitoring; parallel processing;
fLanguage :
English
Journal_Title :
Proceedings of the IEEE
Publisher :
ieee
ISSN :
0018-9219
Type :
jour
DOI :
10.1109/JPROC.2004.840300
Filename :
1386660
Link To Document :
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