Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/519572
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dc.coverage.spatialNetwork optimization and security enhancement for cloud based e learning platforms
dc.date.accessioned2023-10-22T05:19:18Z-
dc.date.available2023-10-22T05:19:18Z-
dc.identifier.urihttp://hdl.handle.net/10603/519572-
dc.description.abstractnewline This study compared the performance of various cryptographic algorithms, including Elliptic Curve Cryptography (ECC), Advanced Encryption Standard (AES), Two Fish, Blowfish, Data Encryption Standard (DES), Triple Data Encryption Standard (TDES), and role-based access control, to ensure the security of cloud data storage used for educational purposes in the NPTEL database (RBAC). The cloud-based network optimization data transmission is explained by network optimization ROA. The performance of this technique has been evaluated using a variety of requests and metrics. Compared to PSO, GA, and Firefly, we consumed less RAM. This ROA manages incremental server load sharing to keep servers from becoming overwhelmed or idle. Based on availability and comparison logic, it ensures that new users are assigned to the most powerful server.
dc.format.extentxviii, 142 p.
dc.languageEnglish
dc.relationp. 124-141
dc.rightsuniversity
dc.titleNetwork optimization and security enhancement for cloud based e learning platforms
dc.title.alternative
dc.creator.researcherSoundhara Raja Pandian R
dc.subject.keywordE-Learning
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.subject.keywordNPTEL
dc.subject.keywordRider Optimization Algorithm
dc.description.note
dc.contributor.guideChristopher Columbus C and Sree Rathna Lakshmi N V S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Electrical Engineering
dc.date.registered
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions21 cm.
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Electrical Engineering

Files in This Item:
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01_title.pdfAttached File29.6 kBAdobe PDFView/Open
02_prelim_pages.pdf387.06 kBAdobe PDFView/Open
03_content.pdf26.79 kBAdobe PDFView/Open
04_abstract.pdf20.37 kBAdobe PDFView/Open
05_chapter 1.pdf337.73 kBAdobe PDFView/Open
06_chapter 2.pdf91.79 kBAdobe PDFView/Open
07_chapter 3.pdf374.71 kBAdobe PDFView/Open
08_chapter 4.pdf800.34 kBAdobe PDFView/Open
09_annexures.pdf149.05 kBAdobe PDFView/Open
80_recommendation.pdf91.06 kBAdobe PDFView/Open


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