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A Reinforcement Learning Framework for Knowledge-Defined Networking

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253555" target="_blank" >RIV/61989100:27240/23:10253555 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/23:10253555

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10333287" target="_blank" >https://ieeexplore.ieee.org/document/10333287</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICUMT61075.2023.10333287" target="_blank" >10.1109/ICUMT61075.2023.10333287</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Reinforcement Learning Framework for Knowledge-Defined Networking

  • Original language description

    The deployment of 6G networks is expected to bring fundamental improvements to network architectures and a focus on incorporating artificial intelligence (AI) technologies. The paper explores the concept of knowledge-defined networking (KDN), where the intelligence of the network resides in the knowledge plane (KP), resulting from a combination of software-defined networking (SDN), network telemetry, and machine learning (ML) algorithms. The paper highlights the use of programming protocol-independent packet processors (P4), a technology which enables SDN networks, and emphasizes the importance of in-band network telemetry (INT) for providing real-time network information. The paper also draws a connection between P4-SDN network architecture and reinforcement Learning (RL), exhibiting how network components and existing techniques can be mapped onto RL principles. The potential of AI-driven network orchestration and the interpretation of networks as AI-based systems are also discussed.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

  • ISBN

    979-8-3503-9328-6

  • ISSN

    2157-0221

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    152-156

  • Publisher name

    IEEE

  • Place of publication

    Piscataway

  • Event location

    Ghent

  • Event date

    Oct 30, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article