Academic Journal

Network Traffic Analysis in Software-Defined Networking Using RYU Controller.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Network Traffic Analysis in Software-Defined Networking Using RYU Controller.
Συγγραφείς: Bhardwaj, Shanu, Girdhar, Ashish
Πηγή: Wireless Personal Communications; Oct2023, Vol. 132 Issue 3, p1797-1818, 22p
Θεματικοί όροι: Network performance, Computer network traffic, Software-defined networking, Wireless communications
Περίληψη: Software-Defined Networking (SDN) has emerged as a promising paradigm to enhance network control and management by decoupling the planes. With SDN, the centralized controller plays a critical role in managing network resources and traffic flows. Throughout the most recent couple of years, networks turned out to be more imaginative for developing different applications with the help of SDN. Network traffic analysis is a vital task in understanding network behaviour, identifying anomalies, and optimizing network performance. To deal with the load of changes in the networking industry, there is an extraordinary requirement for a productive SDN controller to work on the usage of network resources for a better presentation of the network. Therefore, the proposed approach leverages the RYU controller, an open-source SDN controller framework, to collect and analyse network traffic data. By utilizing RYU's capabilities, we can dynamically monitor and capture network traffic statistics, such as bandwidth, throughput, packet counts, and Round trip time (RTT). These statistics provide valuable insights into network performance, and traffic patterns. By leveraging real-time traffic analysis, we can dynamically adjust routing paths, and allocate network resources efficiently. Hence, the proposed work assesses the development of SDN architecture through a network topology and then, implementation of RYU controller has been done to evaluate various network performance parameters. To evaluate the effectiveness of our approach, we conduct experiments using a simulated SDN environment. We compare the performance parameters of our traffic analysis techniques with traditional methods and showcase the advantages of utilizing SDN and the Ryu controller for network traffic analysis. The results demonstrate that our approach provides accurate and timely insights into network traffic behaviour, facilitating efficient network management. In conclusion, this study highlights the significance of network traffic analysis in SDN environments and demonstrates the effectiveness of the Ryu controller for extracting valuable insights from network traffic data. [ABSTRACT FROM AUTHOR]
Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  – Url: https://dx.doi.org/doi:10.1007/s11277-023-10680-1
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  Data: Wireless Personal Communications; Oct2023, Vol. 132 Issue 3, p1797-1818, 22p
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  Data: Software-Defined Networking (SDN) has emerged as a promising paradigm to enhance network control and management by decoupling the planes. With SDN, the centralized controller plays a critical role in managing network resources and traffic flows. Throughout the most recent couple of years, networks turned out to be more imaginative for developing different applications with the help of SDN. Network traffic analysis is a vital task in understanding network behaviour, identifying anomalies, and optimizing network performance. To deal with the load of changes in the networking industry, there is an extraordinary requirement for a productive SDN controller to work on the usage of network resources for a better presentation of the network. Therefore, the proposed approach leverages the RYU controller, an open-source SDN controller framework, to collect and analyse network traffic data. By utilizing RYU's capabilities, we can dynamically monitor and capture network traffic statistics, such as bandwidth, throughput, packet counts, and Round trip time (RTT). These statistics provide valuable insights into network performance, and traffic patterns. By leveraging real-time traffic analysis, we can dynamically adjust routing paths, and allocate network resources efficiently. Hence, the proposed work assesses the development of SDN architecture through a network topology and then, implementation of RYU controller has been done to evaluate various network performance parameters. To evaluate the effectiveness of our approach, we conduct experiments using a simulated SDN environment. We compare the performance parameters of our traffic analysis techniques with traditional methods and showcase the advantages of utilizing SDN and the Ryu controller for network traffic analysis. The results demonstrate that our approach provides accurate and timely insights into network traffic behaviour, facilitating efficient network management. In conclusion, this study highlights the significance of network traffic analysis in SDN environments and demonstrates the effectiveness of the Ryu controller for extracting valuable insights from network traffic data. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11277-023-10680-1
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        Text: English
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      – SubjectFull: Network performance
        Type: general
      – SubjectFull: Computer network traffic
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      – SubjectFull: Software-defined networking
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              Text: Oct2023
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