Combination of Advanced Reservation and Resource Periodic Arrangement for RMSA in EON with Deep Reinforcement Learning

• Autorzy: Silaban R. J. , Alaydrus Mudrik , Umaisaroh U.

Identyfikatory

DOI

10.24425/ijet.2023.146500

• Języki publikacji: EN

Abstrakty

EN

The Elastic Optical Networks (EON) provide a solution to the massive demand for connections and extremely high data traffic with the Routing Modulation and Spectrum Assignment (RMSA) as a challenge. In previous RMSA research, there was a high blocking probability because the route to be passed by the K-SP method with a deep neural network approach used the First Fit policy, and the modulation problem was solved with Modulation Format Identification (MFI) or BPSK using Deep Reinforcement Learning. The issue might be apparent in spectrum assignment because of the influence of Advanced Reservation (AR) and Resource Periodic Arrangement (RPA), which is a decision block on a connection request path with both idle and active data traffic. The study’s limitation begins with determining the modulation of m = 1 and m = 4, followed by the placement of frequencies, namely 13 with a combination of standard block frequencies 41224–24412, so that the simulation results are less than 0.0199, due to the combination of block frequency slices with spectrum allocation rule techniques.

Słowa kluczowe

EN

Elastic Optical Networks (EON); Routing Modulation and Spectrum Assignment (RMSA); Advanced Reservation (AR); Resource Periodic Arrangement (RPA)

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2023
• Tom: Vol. 69, No. 3
• Strony: 515--522
• Opis fizyczny: Bibliogr. 36 poz., rys., tab., wykr.

Twórcy

autor

Silaban R. J.

• Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia

autor

Alaydrus Mudrik

• Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia

autor

Umaisaroh U.

• Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).