Processing and classifying IP packet data on the Internet based on machine learning

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dc.contributor.authorVuong, Xuan Chi
dc.contributor.authorNguyen, Kim Quoc
dc.date.accessioned2024-08-22T03:51:44Z
dc.date.accessioned2024-08-29T02:20:09Z
dc.date.available2024-08-22T03:51:44Z
dc.date.available2024-08-29T02:20:09Z
dc.date.issued2024
dc.description11 p.
dc.description.abstractNowadays, the continuous development of information technology, communication over the Internet is increasing rapidly, and network congestion has become an alarming issue. To develop communication network infrastructure in a large city, a country, or globally, streamlining and controlling network data flow to optimize communication processes and minimize network congestion is crucial and necessary. In this study, the authors analyze and process data according to the delay of Internet Protocol (IP) packets, using machine learning models with the Random Forest (RF) and the Support Vector Machines (SVM) method to classify IP packets. The primary goal of classifying packets by delay is to optimize network performance by prioritizing processing of low-delay packets, ensuring stable and uninterrupted online services such as video streaming and voice calls. Furthermore, it is easy to manage and control packet traffic, hence minimizing network congestion at the router.
dc.identifier.citationNguyen Tat Thanh University. (2024). Journal of Science and Technology - NTTU, Volume 7, Issue 2. ISSN 2615-9015.
dc.identifier.issn2615-9015
dc.identifier.urihttps://repository.ntt.edu.vn/handle/298300331/50051
dc.language.isoen
dc.publisherNguyen Tat Thanh University
dc.relation.ispartofseriesJournal of Science and Technology - NTTU; Vol.7, No. 2
dc.subjectIP packet classification
dc.subjectIP network
dc.subjectNetwork congestion
dc.subjectMachine learning
dc.subjectRandom forest
dc.subjectMạng IP
dc.titleProcessing and classifying IP packet data on the Internet based on machine learning
dc.typeArticle

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