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dc.contributor.author강경태-
dc.date.accessioned2019-04-03T00:06:21Z-
dc.date.available2019-04-03T00:06:21Z-
dc.date.issued2015-08-
dc.identifier.citation2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), and 2015 IEEE 12th International Conf on Embedded Software and Systems (ICESS), Page. 1051-1056en_US
dc.identifier.isbn978-1-4799-8937-9-
dc.identifier.urihttp://ieeexplore.ieee.org/document/7336308/-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/101407-
dc.description.abstractApplication launch and loading times are important determinants of user experience in the personal computing environment. Since these delays largely depend on the performance of secondary storage, they can be reduced by prefetching disk blocks. However, existing prefetching schemes for general workloads incur a significant overhead in analyzing correlations between blocks so as to choose the blocks to prefetch, and, more significantly, these analyses lack accuracy. We propose a lightweight prefetcher called ClusterFetch which records the sequences of I/O requests that are triggered by file requests during launch and loading. When the same application is run again, the disk blocks that correspond to the stored sequences of I/O requests are prefetched when the related files are opened. Experimental results show that ClusterFetch can reduce application launch times by up to 30.9%, and loading times by up to 15.9%.en_US
dc.description.sponsorshipThis work was partly supported by a grant from the Institute for Information & Communications Technology Promotion (IITP), funded by the Korean government (MSIP) (No. B0101-15-0557, Resilient Cyber-Physical Systems Research), and partly supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the MSIP (NRF-2013R1A1A1059188). The corresponding author is D. Lee.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.subjectClusterFetchen_US
dc.subjectapplication loadingen_US
dc.subjectprefetchingen_US
dc.subjectdisk I/O schedulingen_US
dc.titleClusterFetch: A Lightweight Prefetcher that Responds to Intensive Disk Read Patternsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/HPCC-CSS-ICESS.2015.258-
dc.relation.page1051-1056-
dc.contributor.googleauthorRyu, J-
dc.contributor.googleauthorJeong, H-
dc.contributor.googleauthorLee, D-
dc.contributor.googleauthorShin, H-
dc.contributor.googleauthorKang, K-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidktkang-
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