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» Dynamic Fractional Resource Scheduling for cluster platforms
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CCGRID
2008
IEEE
14 years 2 months ago
Grid Differentiated Services: A Reinforcement Learning Approach
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
CCGRID
2003
IEEE
14 years 1 months ago
GridFlow: Workflow Management for Grid Computing
Grid computing is becoming a mainstream technology for large-scale distributed resource sharing and system integration. Workflow management is emerging as one of the most importan...
Junwei Cao, Stephen A. Jarvis, Subhash Saini, Grah...
CCGRID
2005
IEEE
14 years 1 months ago
A novel workload migration scheme for heterogeneous distributed computing
Dynamically partitioning of adaptive applications and migration of excess workload from overloaded processors to underloaded processors during execution are critical techniques ne...
Yawei Li, Zhiling Lan
JSSPP
2004
Springer
14 years 1 months ago
Enhancements to the Decision Process of the Self-Tuning dynP Scheduler
The self-tuning dynP scheduler for modern cluster resource management systems switches between different basic scheduling policies dynamically during run time. This allows to reac...
Achim Streit
FGCS
2007
99views more  FGCS 2007»
13 years 7 months ago
Mining performance data for metascheduling decision support in the Grid
: Metaschedulers in the Grid needs dynamic information to support their scheduling decisions. Job response time on computing resources, for instance, is such a performance metric. ...
Hui Li, David L. Groep, Lex Wolters