Asymptotic Load Balancing Algorithm for Many Task Scheduling

dc.contributor.authorOncioiu, Anamaria-Raluca
dc.contributor.authorPop, Florin
dc.contributor.authorEsposito, Christian
dc.date.accessioned2023-05-31T10:52:42Z
dc.date.available2023-05-31T10:52:42Z
dc.date.issued2019
dc.description.abstractCloud computing can enable the unraveling of new scientific breakthroughs. We will eventually arrive to compute overwhelmingly large sizes of information, larger than we ever thought about it. Better scheduling algorithms are the key to process Big Data. This paper presents a load balancing scheduling algorithm for Many Task Computing using the computational resources from Cloud, in order to process a huge number of tasks with a finite number of resources. As such, the algorithm can be also used for Big Data, because it scales easily for big applications if we put a load balancing algorithm on top of virtual machines. We impose an upper bound of one for the maximum nodes that can carry an arbitrary job without executing it and we show that this statement holds by simulating the algorithm in MTS2 (Many Task Scheduling Simulator). We also show that the algorithm’s overlay performs even better when there are multiple nodes and we discuss about choosing the best local scheduling policy for the working nodes.
dc.identifier.doi10.1007/978-3-030-31831-4_10
dc.identifier.isiWOS:000545267200010
dc.identifier.urihttps://dspace.apps.spero.ici.ro/handle/123456789/136
dc.identifier.urlhttps://www.springerprofessional.de/en/asymptotic-load-balancing-algorithm-for-many-task-scheduling/17209090
dc.language.isoen
dc.publisherSpringer
dc.relation.conferenceInternational Conference on Ad-Hoc Networks and Wireless, 1-3.10.2019, Luxembourg
dc.relation.firstpage136
dc.relation.isbn978-3-030-31831-4
dc.relation.issn0302-9743
dc.relation.lastpage149
dc.relation.volume11803
dc.titleAsymptotic Load Balancing Algorithm for Many Task Scheduling
dc.typeConference paper
dc.type.extendedISI
dc.type.extendedExternal
dc.type.extendedEU
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