Wieder, Philipp

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[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.lastpage","9"],["dc.contributor.author","Yang, Song"],["dc.contributor.author","Wieder, Philipp"],["dc.contributor.author","Aziz, Muzzamil"],["dc.contributor.author","Yahyapour, Ramin"],["dc.contributor.author","Fu, Xiaoming"],["dc.date.accessioned","2018-04-11T11:14:07Z"],["dc.date.available","2018-04-11T11:14:07Z"],["dc.date.issued","2017"],["dc.description.abstract","Customers often suffer from the variability of data access time in cloud storage service, caused by network congestion, load dynamics, etc. One solution to guarantee a reliable latency-sensitive service is to issue requests with multiple download/upload sessions, accessing the required data (replicas) stored in one or more servers. In order to minimize storage costs, how to optimally allocate data in a minimum number of servers without violating latency guarantees remains to be a crucial issue for the cloud provider to tackle. In this paper, we study the latency-sensitive data allocation problem for cloud storage. We model the data access time as a given distribution whose Cumulative Density Function (CDF) is known, and prove that this problem is NP-hard. To solve it, we propose both exact Integer Nonlinear Program (INLP) and Tabu Search-based heuristic. The proposed algorithms are evaluated in terms of the number of used servers, storage utilization and throughput utilization."],["dc.identifier.doi","10.23919/INM.2017.7987258"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/13221"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","IEEE"],["dc.relation.conference","2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)"],["dc.relation.eventend","2017-05-12"],["dc.relation.eventlocation","Lisbon, Portugal"],["dc.relation.eventstart","2017-05-08"],["dc.relation.isbn","978-3-901882-89-0"],["dc.relation.isbn","978-3-901882-89-0"],["dc.relation.ispartof","2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)"],["dc.relation.orgunit","Gesellschaft für wissenschaftliche Datenverarbeitung"],["dc.title","Latency-Sensitive Data Allocation for cloud storage"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

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