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ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
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Data sources: DBLP
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A hierarchical AI-based control plane solution for multi-technology deterministic networks

Authors: Pietro G. Giardina; Péter Szilágyi; Carla-Fabiana Chiasserini; Jose Luis Carcel; Luis Velasco 0001; Salvatore Spadaro; Fernando Agraz; +6 Authors

A hierarchical AI-based control plane solution for multi-technology deterministic networks

Abstract

Following the Industry 4.0 vision of a full digitiSation of the industry, time-critical services and applications, allowing network infrastructures to deliver information with determinism and reliability, are becoming more and more relevant for a set of vertical sectors. As a consequence, deterministic network solutions are progressively emerging, albeit they are still bounded to specific technological domains. Even considering the existence of interconnected deterministic networks, the provision of an end-to-end (E2E) deterministic service over them must rely on a specific control plane architecture, capable of seamlessly integrate and control the underlying multi-technology data plane. In this work, we envision such a control plane solution, extending previous works and exploiting several innovations and novel architectural concepts. The proposed control architecture is service-centric, in order to provide the necessary flexibility, scalability, and modularity to deal with a heterogenous data plane. The architecture is hierarchical and encompasses a set of management platforms to interact with specific network technologies overarched by an E2E platform for the management, monitoring, and control of E2E deterministic services. Furthermore, Artificial Intelligence (AI) and Digital Twinning are used to enable network predictability and automation, as well as smart resource allocation, to ensure service reliability in dynamic scenarios where existing services may terminate and new ones may need to be deployed.

Countries
Spain, Italy
Keywords

Control plane, TSN, Digital twins (Computer simulation), Time sensitiveness, Network Determinism, SNS, Cross-domain, Predictability, Reliability, PREDICT-6G, Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, AI/ML; Time deterministic networks; Time sensitive networks; Industry 4.0; Machine Learning; Control plane; Control Platform; 6G, Ordinadors, Xarxes d' -- Disseny i construcció, DetNet, Rèpliques digitals (Simulació per ordinador), RAW, Control Plane, Computer networks -- Design and construction, Network determinism, Time-sensitiveness, 6G

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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