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A Model-Based Scheduling Framework for Enhancing Robustness
(2018)
Scheduling algorithms used for dynamic scheduling of tasks in a distributed system are generally evaluated on their performance, i.e., their degree of achieving a desired outcome or metric. They may also be evaluated on ...
Enhancing Scheduling Robustness with Partial Task Completion Feedback and Resource Requirement Biasing
(2019)
Performance and robustness of dynamic scheduling algorithms are evaluated in the presence of errors in the tasks’ resource requirements. Previous work found that incorporating task completion events ...
Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing
(2018-12)
Scheduling tasks in a distributed system (e.g., cloud computing) in order to optimize an objective such as minimizing deadline misses has been a topic of research for decades. Such a problem is proven NP Complete even ...