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Memory optimization for file systems

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dc.date.accessioned 2016-03-22T15:41:10Z und
dc.date.accessioned 2017-10-24T12:24:08Z
dc.date.available 2016-03-22T15:41:10Z und
dc.date.available 2017-10-24T12:24:08Z
dc.date.issued 2016-03-22T15:41:10Z
dc.identifier.uri http://radr.hulib.helsinki.fi/handle/10138.1/5392 und
dc.identifier.uri http://hdl.handle.net/10138.1/5392
dc.title Memory optimization for file systems en
ethesis.department.URI http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14
ethesis.department Institutionen för datavetenskap sv
ethesis.department Department of Computer Science en
ethesis.department Tietojenkäsittelytieteen laitos fi
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingfors universitet sv
ethesis.university University of Helsinki en
ethesis.university Helsingin yliopisto fi
dct.creator Pandit, Rakesh
dct.issued 2016
dct.language.ISO639-2 eng
dct.abstract Aim of this thesis is to investigate whether performing secondary storage memory optimization in an embedded system by improving on-disk patterns generated by input/output (I/O) operations, while system is still operational or online, can increase performance and life time. Complex workloads on embedded devices result in non optimal I/O patterns, and these patterns then increase power consumption in addition to reducing read/write throughput for future requests. Because of limited resources and nature of use case, in certain situations it is impossible to take system or storage device offline and run optimizations for prolonged period of time. This work achieves its goal by designing a daemon which monitors I/O operations on storage device inside operating system and then based on certain pre-defined criteria, moves data into contiguous spaces and aligns them based on storage device characteristics when system is idle. After implementing daemon, file system benchmarking is used to evaluate it based on file system performance. en
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
ethesis.degreeprogram Networking and Service en
dct.identifier.urn URN:NBN:fi-fe2017112251013
dc.type.dcmitype Text

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