SDN-based Self-Configuration for Time-Sensitive IoT Networks

Bülbül, Nurefşan Sertbas; Ergenç, Doğanalp; Fischer, Mathias

doi:10.1109/lcn52139.2021.9524979

Cited by 18 publications

(3 citation statements)

References 17 publications

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“…Extending these insights, Bulbu et al [80] present the implementation of a SDN architecture tailored for the self-configuration of time-sensitive IoT networks. This initiative aims to enhance network management in scenarios where time synchronization and precision are crucial.…”

Section: Time-sensitive Iiotmentioning

confidence: 99%

A Survey on AI-Empowered Softwarized Industrial IoT Networks

Rojas,

Carrascal,

Lopez-Pajares

et al. 2024

Electronics

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The future generation of mobile networks envision Artificial Intelligence (AI) and the Internet of Things (IoT) as key enabling technologies that will foster the emergence of sophisticated use cases, with the industrial sector being one to benefit the most. This survey reviews related works in this field, with a particular focus on the specific role of network softwarization. Furthermore, the survey delves into their context and trends, categorizing works into several types and comparing them based on their contribution to the advancement of the state of the art. Since our analysis yields a lack of integrated practical implementations and a potential desynchronization with current standards, we finalize our study with a summary of challenges and future research ideas.

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Section: Time-sensitive Iiotmentioning

confidence: 99%

A Survey on AI-Empowered Softwarized Industrial IoT Networks

Rojas,

Carrascal,

Lopez-Pajares

et al. 2024

Electronics

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“…In [ 96 ], the authors present a novel self-configuration model, based on software-defined networks (SDN) for time-sensitive networks. In existing configuration methods, end nodes send their data to a central management node.…”

Section: Literature Review and Analysismentioning

confidence: 99%

Self-* Capabilities of Cloud-Edge Nodes: A Research Review

S-Julián

Lacalle

Vaño

et al. 2023

Sensors

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Most recent edge and fog computing architectures aim at pushing cloud-native traits at the edge of the network, reducing latency, power consumption, and network overhead, allowing operations to be performed close to data sources. To manage these architectures in an autonomous way, systems that materialize in specific computing nodes must deploy self-* capabilities minimizing human intervention across the continuum of computing equipment. Nowadays, a systematic classification of such capabilities is missing, as well as an analysis on how those can be implemented. For a system owner in a continuum deployment, there is not a main reference publication to consult to determine what capabilities do exist and which are the sources to rely on. In this article, a literature review is conducted to analyze the self-* capabilities needed to achieve a self-* equipped nature in truly autonomous systems. The article aims to shed light on a potential uniting taxonomy in this heterogeneous field. In addition, the results provided include conclusions on why those aspects are too heterogeneously tackled, depend hugely on specific cases, and shed light on why there is not a clear reference architecture to guide on the matter of which traits to equip the nodes with.

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“…Ref. [67] proposed a novel approach for automatic configuration based on SDN. Newly added flows can be directly forwarded on the default path, and then migrated to the optimal path by the SDN controller based on traffic characteristics and network resource conditions.…”

mentioning

confidence: 99%

Recent Advances in Time-Sensitive Network Configuration Management: A Literature Review

Shi,

Tu,

et al. 2023

JSAN

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At present, many network applications are seeking to implement Time-Sensitive Network (TSN) technology, which not only furnishes communication transmission services that are deterministic, low-latency, highly dependable, and have ample bandwidth, but also enables unified configuration management, permitting different network types to function under a single management system. These characteristics enable it to be widely used in many fields such as industrial sensor and actuator networks, in-vehicle networks, data center networks, and edge computing. Nonetheless, TSN’s configuration management faces numerous difficulties and challenges related to network deployment, automated operation, and maintenance, as well as real-time and safety assurance, rendering it exceedingly intricate. In recent years, some studies have been conducted on TSN configuration management, encompassing various aspects such as system design, key technologies for configuration management, protocol enhancement, and application development. Nevertheless, there is a dearth of systematic summaries of these studies. Hence, this article aims to provide a comprehensive overview of TSN configuration management. Drawing upon more than 70 relevant publications and the pertinent standards established by the IEEE 802.1 TSN working group, we first introduce the system architecture of TSN configuration management from a macro perspective and then explore specific technical details. Additionally, we demonstrate its application scenarios through practical cases and finally highlight the challenges and future research directions. We aspire to provide a comprehensive reference for peers and new researchers interested in TSN configuration management.

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SDN-based Self-Configuration for Time-Sensitive IoT Networks

Cited by 18 publications

References 17 publications

A Survey on AI-Empowered Softwarized Industrial IoT Networks

A Survey on AI-Empowered Softwarized Industrial IoT Networks

Self-* Capabilities of Cloud-Edge Nodes: A Research Review

Recent Advances in Time-Sensitive Network Configuration Management: A Literature Review

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