Enhancing Scheduling Robustness with Partial Task Completion Feedback and Resource Requirement Biasing

Grounds, Nicolas; Antonio, John K.

Enhancing Scheduling Robustness with Partial Task Completion Feedback and Resource Requirement Biasing

dc.contributor.author	Grounds, Nicolas
dc.contributor.author	Antonio, John K.
dc.date.accessioned	2021-05-17T15:16:10Z
dc.date.available	2021-05-17T15:16:10Z
dc.date.issued	2019
dc.description.abstract	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 from the actual distributed system into the algorithms’ model of the system was crucial for achieving robustness. In the present paper, various degrees of feedback, rather than simply all-or-none, are evaluated using the same simulated studies as in previous work and a proposed strategy for biasing model tasks’ resource requirement information is proposed in order to counteract the most egregious effects of model error on performance.	en_US
dc.description.peerreview	Yes	en_US
dc.identifier.citation	Grounds, N. and Antonio, J.K. (2019). Enhancing Scheduling Robustness with Partial Task Completion Feedback and Resource Requirement Biasing. In Hamid R. Arabnia, et al. (Ed). Proceedings of the 2019 International Conference on Parallel and Distributed Processing Techniques & Applications, Las Vegas, July 29-August 1 2019 (pp. 19-25). CSREA Press.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/329595
dc.language	en_US	en_US
dc.subject	Distributed System	en_US
dc.subject	Scheduling	en_US
dc.subject	Performance	en_US
dc.subject	Robustness	en_US
dc.subject	Biasing	en_US
dc.title	Enhancing Scheduling Robustness with Partial Task Completion Feedback and Resource Requirement Biasing	en_US
dc.type	Other	en_US
ou.group	Gallogly College of Engineering::School of Computer Science	en_US