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dc.contributor.authorGedik, B.en_US
dc.date.accessioned2016-02-08T10:44:29Z
dc.date.available2016-02-08T10:44:29Z
dc.date.issued2014en_US
dc.identifier.issn0018-9340
dc.identifier.urihttp://hdl.handle.net/11693/25425
dc.description.abstractThis paper introduces an adaptive compression algorithm for transfer of data streams across operators in stream processing systems. The algorithm is adaptive in the sense that it can adjust the amount of compression applied based on the bandwidth, CPU, and workload availability. It is discriminative in the sense that it can judiciously apply partial compression by selecting a subset of attributes that can provide good reduction in the used bandwidth at a low cost. The algorithm relies on the significant differences that exist among stream attributes with respect to their relative sizes, compression ratios, compression costs, and their amenability to application of custom compressors. As part of this study, we present a modeling of uniform and discriminative mixing, and provide various greedy algorithms and associated metrics to locate an effective setting when model parameters are available at run-time. Furthermore, we provide online and adaptive algorithms for real-world systems in which system parameters that can be measured at run-time are limited. We present a detailed experimental study that illustrates the superiority of discriminative mixing over uniform mixing. © 2013 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE Transactions on Computersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TC.2013.103en_US
dc.subjectAdaptive compressionen_US
dc.subjectStream compressionen_US
dc.subjectAdaptive algorithmsen_US
dc.subjectAlgorithmsen_US
dc.subjectBandwidthen_US
dc.subjectBandwidth compressionen_US
dc.subjectData communication systemsen_US
dc.subjectData transferen_US
dc.subjectMixingen_US
dc.subjectOnline systemsen_US
dc.subjectParameter estimationen_US
dc.subjectReal time systemsen_US
dc.subjectGreedy algorithmsen_US
dc.subjectModel parametersen_US
dc.subjectPartial compressionsen_US
dc.subjectReal-world systemen_US
dc.subjectRelative sizesen_US
dc.subjectData compressionen_US
dc.titleDiscriminative fine-grained mixing for adaptive compression of data streamsen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage2228en_US
dc.citation.epage2244en_US
dc.citation.volumeNumber63en_US
dc.citation.issueNumber9en_US
dc.identifier.doi10.1109/TC.2013.103en_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US


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