2011
DOI: 10.1007/978-3-642-22947-3_11
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CAD: An Efficient Data Management and Migration Scheme across Clouds for Data-Intensive Scientific Applications

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Cited by 4 publications
(5 citation statements)
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References 28 publications
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“…The scheduler needs to allocate the workload to available resources, while dynamically balancing the workload [88]. Consequently, it helps in maximum resource utilization, which results in improving the overall system performance [3,18,72,96,97]. However, the scheduler also needs to consider all QoS constraints as requested by the cloud users [40].…”
Section: Load Balancingmentioning
confidence: 98%
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“…The scheduler needs to allocate the workload to available resources, while dynamically balancing the workload [88]. Consequently, it helps in maximum resource utilization, which results in improving the overall system performance [3,18,72,96,97]. However, the scheduler also needs to consider all QoS constraints as requested by the cloud users [40].…”
Section: Load Balancingmentioning
confidence: 98%
“…[12] x Dynamic resource provisioning techniques [64] x x x CMSA [72] x x Time-Cost trade-off workflow scheduling algorithm [57] x x x CAD [18] x CHPS [2] x SHEFT [63] x x Heuristic designing scheduling framework [65] x x…”
Section: System Functionality Challenges Form Profitability Aspectmentioning
confidence: 99%
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“…Finally, Yang et al describe methods for improving both performance and fault tolerance of messaging in cloud system [21], [22]. Such methods might be useful in the remote I/O system we describe.…”
Section: Related Workmentioning
confidence: 99%
“…Data warehouses (Chaudhuriet al,2011)are moreandmorebecomingakeycomponentof data-intensive systems,like,forinstance,recent Cloud environments (Buyyaet al,2011),where data explosionplaysacriticalroleandwhose managementrepresentsamajorresearchchallenge (Hsu et al, 2011). Due to this evident relevance,knowledge discovery and management(e.g., (Cuzzocrea,2009))representaviable solutiontotheproblemofenhancingtheway weactuallyaccess,manageandexplorelarge amounts of multidimensional data stored in datawarehouses.Supportingadvanced query answeringandactionable knowledge extraction fromdatawarehousescanthusbereasonably intendedasoneofthemostchallengingissues fornext-generationdatawarehouseresearch.…”
Section: Introductionmentioning
confidence: 99%