As the complexity, distribution, and heterogeneity of networks continue to grow, how to architect and monitor of these networking environments is becoming an increasingly critical open issue. Digital twins, which can replicate the structure and behavior of a physical network, are seen as potential solution to address the problem. While reference architectures for digital twins exist in other fields, a comprehensive reference architecture for the networking context has yet to be developed. This paper discusses the need for such a reference architecture and outlines the key elements necessary for its design. We present the findings of a preliminary survey that explores the need for a network digital twin reference architecture, the crucial information it should include, and practical insights into its design. The survey results confirm that existing standards are inadequate for modeling network digital twins, outlining the necessity of a new reference architecture. We then articulate our position on the need for a reference architecture for network digital twins, focusing on three main aspects, namely: (i) digital twins of what, (ii) for what, and (iii) how to deploy them. We then proceed to delineate the fundamental obstacles that a reference architecture must confront, in tandem with the essential characteristics it needs to embody to successfully navigate these challenges. As conclusion, we present our vision for the reference architecture and outline the main research steps we plan to take to address this open problem. Our ultimate goal is to tightly collaborate both with the networking and digital twin software architecture communities to jointly establish a sound network digital twin architecture of the future.

Designing a Future-Proof Reference Architecture for Network Digital Twins / Verdecchia R.; Scommegna L.; Vicario E.; Pecorella T.. - ELETTRONICO. - 14590:(2024), pp. 287-306. (Intervento presentato al convegno 17th European Conference on Software Architecture, ECSA 2023 tenutosi a tur nel 2023) [10.1007/978-3-031-66326-0_18].

Designing a Future-Proof Reference Architecture for Network Digital Twins

Verdecchia R.;Scommegna L.;Vicario E.;Pecorella T.
2024

Abstract

As the complexity, distribution, and heterogeneity of networks continue to grow, how to architect and monitor of these networking environments is becoming an increasingly critical open issue. Digital twins, which can replicate the structure and behavior of a physical network, are seen as potential solution to address the problem. While reference architectures for digital twins exist in other fields, a comprehensive reference architecture for the networking context has yet to be developed. This paper discusses the need for such a reference architecture and outlines the key elements necessary for its design. We present the findings of a preliminary survey that explores the need for a network digital twin reference architecture, the crucial information it should include, and practical insights into its design. The survey results confirm that existing standards are inadequate for modeling network digital twins, outlining the necessity of a new reference architecture. We then articulate our position on the need for a reference architecture for network digital twins, focusing on three main aspects, namely: (i) digital twins of what, (ii) for what, and (iii) how to deploy them. We then proceed to delineate the fundamental obstacles that a reference architecture must confront, in tandem with the essential characteristics it needs to embody to successfully navigate these challenges. As conclusion, we present our vision for the reference architecture and outline the main research steps we plan to take to address this open problem. Our ultimate goal is to tightly collaborate both with the networking and digital twin software architecture communities to jointly establish a sound network digital twin architecture of the future.
2024
Proceedings of the 17th European Conference on Software Architecture, ECSA 2023
17th European Conference on Software Architecture, ECSA 2023
tur
2023
Verdecchia R.; Scommegna L.; Vicario E.; Pecorella T.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1400264
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