Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

Task scheduling is an important activity in parallel and distributed computing environment like grid because the performance depends on it. Task scheduling gets affected by behavioral and primary uncertainties. Behavioral uncertainty arises due to variability in the workload characteristics, size of...

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Bibliographic Details
Main Authors: Bhargavi K., Shiva Sajjan G.
Format: Article
Language:English
Published: Sciendo 2022-09-01
Series:Cybernetics and Information Technologies
Subjects:
dyna-q-learning
grid computing
t2ss
uncertainty
performance
Online Access:https://doi.org/10.2478/cait-2022-0027

Internet

https://doi.org/10.2478/cait-2022-0027

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