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» Resource Allocation in the Grid Using Reinforcement Learning
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NECO
2010
103views more  NECO 2010»
13 years 6 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
ICC
2007
IEEE
126views Communications» more  ICC 2007»
14 years 1 months ago
Responsiveness on the Interactive Grid
The Grid vision promises the secure and dynamic sharing of heterogeneous resources across the Internet. To date the emphasis has been on supercomputing scenarios where a relatively...
Colin Allison, Stuart D. J. Purdie, Alan Miller
CCGRID
2010
IEEE
13 years 8 months ago
Decentralized Resource Availability Prediction for a Desktop Grid
In a desktop grid model, the job (computational task) is submitted for execution in the resource only when the resource is idle. There is no guarantee that the job which has starte...
Karthick Ramachandran, Hanan Lutfiyya, Mark Perry
ICS
2011
Tsinghua U.
12 years 11 months ago
Predictive coordination of multiple on-chip resources for chip multiprocessors
Efficient on-chip resource management is crucial for Chip Multiprocessors (CMP) to achieve high resource utilization and enforce system-level performance objectives. Existing mul...
Jian Chen, Lizy Kurian John
HCW
2000
IEEE
13 years 12 months ago
Master/Slave Computing on the Grid
Resource selection is fundamental to the performance of master/slave applications. In this paper, we address the problem of promoting performance for distributed master/slave appl...
Gary Shao, Francine Berman, Richard Wolski