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AuthorNoroozOliaee, MohammadJavad
AuthorHamdaoui, Bechir
AuthorGuizani, Mohsen
AuthorBen Ghorbel, Mahdi
Available date2022-11-10T09:47:27Z
Publication Date2014
Publication NameProceedings - IEEE INFOCOM
ResourceScopus
Resource2-s2.0-84904512102
URIhttp://dx.doi.org/10.1109/INFCOMW.2014.6849261
URIhttp://hdl.handle.net/10576/36187
AbstractWe design a simple and efficient online scheme for scheduling cloud tasks requesting multiple resources, such as CPU and memory. The proposed scheme reduces the queuing delay of the cloud tasks by accounting for their execution time lengths. We also derive bounds on the average queuing delays, and evaluate the performance of our proposed scheme and compare it with those achievable under existing schemes by relying on real Google data traces. Using this data, we show that our scheme outperforms the other schemes in terms of resource utilizations as well as average task queuing delays. 2014 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectDistributed computer systems
Queueing networks
Cloud servers
Derive bounds
Multi-resource
Multiple resources
Queuing delay
Resource utilizations
Task completion time
Task queuing
Scheduling
TitleOnline multi-resource scheduling for minimum task completion time in cloud servers
TypeConference Paper
Pagination375-379
dc.accessType Abstract Only


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