Volume 18 No 6 (2020)
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TRAFFIC ANOMALY DETECTION USING SOFTWARE DEFINED NETWORKING
D. Joseph Jeyakumar, J.Melta, Sangeetha Tupili, Yasaswani Mandiga, M. Murali
Abstract
Emerging information and communication technologies (ICT) megatrends including social media, mobile, big data, and cloud computing will cause more issues for future Internet architecture. High connectivity, dynamic management, and widespread accessibility will be necessary for these. However, traditional techniques that depend on manually configuring proprietary devices are time-consuming, error-prone, and limited in their ability to utilize physical network infrastructure to its fullest. Software-defined networking, or SDN, has been one of the most futuristic concepts for the Internet. The two distinctive features of SDN are enabling programming ability for network app development and separating the control plane from the data plane. In order to facilitate innovative network topologies, SDN is positioned to provide more efficient configuration, enhanced performance, and higher flexibility. In addition, researchers provide an overview of the study's search digital architecture for query search, along with a keyword search ranking rule and, consequently, the top-k-search outcome process methods.
Keywords
Software-defined networking, Traffic Anomaly, Communication Technology,
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