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Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1882
DC FieldValueLanguage
dc.contributor.authorNguyen Duc Thangen_US
dc.date.accessioned2024-11-18T06:54:34Z-
dc.date.available2024-11-18T06:54:34Z-
dc.date.issued2023-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1882-
dc.description.abstractThis dissertation focuses on investigating and assessing different distributed system techniques, especially when it comes to rate-limiting resource protection. The Token Bucket Algorithm, Fixed Window Counter Algorithm, and Sliding Window Log Algorithm are a few of these algorithms. External libraries like Redis for quick value retrieval and Apache Zookeeper for synchronization are integrated into this study. To guarantee accurate data gathering, the benchmarking tests will mainly evaluate the latency, response time, and CPU utilization of each method in a containerized environment. The results show that the best way to deal with the difficulties of distributed rate restriction is to use the Sliding Window Log Algorithm enhanced with LuaScript. Moreover, the application of this rate limiter to a practical scenario yields anticipated outcomes: a decrease in acceptance rates accompanied by reductions in latency, response time, and CPU usage.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectFine-tuning distributeden_US
dc.subjectMulti-scenario performanceen_US
dc.titleFine-tuning distributed rate limiter: a multi-scenario performance evaluationen_US
dc.typeThesisen_US
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item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Computer Science (CS)
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