Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/571003
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2024-06-12T10:21:49Z | - |
dc.date.available | 2024-06-12T10:21:49Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/571003 | - |
dc.description.abstract | newline | |
dc.format.extent | xiv, 214 p | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Enhancement of Reinforcement Learning for Improving Resource Management in Cloud Computing | |
dc.title.alternative | ||
dc.creator.researcher | Lahande, Prathamesh Vijay | |
dc.subject.keyword | Cloud Computing | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Software Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Fault Tolerance | |
dc.subject.keyword | Performance | |
dc.subject.keyword | Reinforcement Learning | |
dc.subject.keyword | Resource Management | |
dc.description.note | ||
dc.contributor.guide | Kaveri, Parag Ravikant | |
dc.publisher.place | Pune | |
dc.publisher.university | Symbiosis International University | |
dc.publisher.institution | Faculty of Computer Studies | |
dc.date.registered | 2019 | |
dc.date.completed | 2024 | |
dc.date.awarded | 2024 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Computer Studies |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 113.64 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.47 MB | Adobe PDF | View/Open | |
03_chapter 1..pdf | 542.41 kB | Adobe PDF | View/Open | |
04_chapter 2..pdf | 755.51 kB | Adobe PDF | View/Open | |
05_chapter 3..pdf | 1.24 MB | Adobe PDF | View/Open | |
06_chapter 4..pdf | 4.51 MB | Adobe PDF | View/Open | |
07_chapter 5..pdf | 322.08 kB | Adobe PDF | View/Open | |
10_annexure..pdf | 3.86 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 591.69 kB | Adobe PDF | View/Open |
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