首页|Study Results from Ain Shams University in the Area of Machine Learning Publishe d (Machine-Learning-Based Traffic Classification in Software-Defined Networks)
Study Results from Ain Shams University in the Area of Machine Learning Publishe d (Machine-Learning-Based Traffic Classification in Software-Defined Networks)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news originating from Cairo,Egypt,by NewsRx cor respondents,research stated,"Many research efforts have gone into upgrading an tiquated communication network infrastructures with better ones to support conte mporary services and applications. Smart networks can adapt to new technologies and traffic trends on their own." Our news correspondents obtained a quote from the research from Ain Shams Univer sity: "Softwaredefined networking (SDN) separates the control plane from the da ta plane and runs programs in one place,changing network management. New techno logies like SDN and machine learning (ML) could improve network performance and QoS. This paper presents a comprehensive research study on integrating SDN with ML to improve network performance and quality-of-service (QoS). The study primar ily investigates ML classification methods,highlighting their significance in t he context of traffic classification (TC). Additionally,traditional methods are discussed to clarify the ML outperformance observed throughout our investigatio n,underscoring the superiority of ML algorithms in SDN TC. The study describes how labeled traffic data can be used to train ML models for appropriately classi fying SDN TC flows. It examines the pros and downsides of dynamic and adaptive T C using ML algorithms. The research also examines how ML may improve SDN securit y."
Ain Shams UniversityCairoEgyptAfri caCybersecurityCyborgsEmerging TechnologiesMachine LearningSoftwareT echnology
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