Time-Sensitive Networking for 5G Fronthaul Networks

Bhattacharjee, Sushmit; Schmidt, Robert; Katsalis, Kostas; Chang, Chia‐Yu; Bauschert, Thomas; Nikaein, Navid

doi:10.1109/icc40277.2020.9149161

Cited by 19 publications

(8 citation statements)

References 15 publications

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“…Thus, TSN-Qbv is more effective when the traffic is scheduled. This has been experimentally validated in our previous work [7]. In the underload scenario, we notice the lowest values of latency in the case of Preemption, which always preempts the lower priority eMBB traffic and prioritizes the URLLC flows.…”

Section: B Evaluationsupporting

confidence: 75%

“…By applying simulations it is demonstrated that contention of high priority traffic can be reduced and the frame delay jitter can be minimized. In [7], we evaluated the performance of Ethernet TSN networks based on IEEE 802.1Qbv and IEEE 802.1Qbu for carrying real fronthaul traffic and benchmarked it against Strict priority and Round Robin scheduling schemes.…”

Section: B Tsn For the Fronthaul-8021cm Profilementioning

confidence: 99%

“…For both the core and the RAN, we use OpenAirInterface (OAI) [9]. For the fronthaul, we use NGFI split 4.5, similar to 3GPP option 7-1 [7]. For this split option, OAI defines a custom format for packetization [62].…”

Section: ) Disaggregated Ran Using Openairinterfacementioning

confidence: 99%

“…In [6], the authors propose to interconnect synchronized TSN domains through an optical backbone. In our previous work [7], we investigated the fronthaul performance when IEEE 802.1Qbv and IEEE 802.1Qbu are applied in the TSN data plane. We provide a detailed analysis of related work and current research activities in the following sections.…”

Section: Introductionmentioning

confidence: 99%

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Network Slicing for TSN-Based Transport Networks

et al. 2021

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In this work, we present and analyze methods and mechanisms for interconnecting a network slice control and management system of the mobile network, with an IEEE Time-Sensitive Network (TSN) control plane. IEEE TSN is gaining momentum as a key technology that is able to provide network service guarantees for Ethernet-based communications. Although Ultra-Reliable Low-Latency Communications (URLLC) have been thoroughly investigated in 5G, incorporating TSN technologies in the Transport Network is expected to unleash the potential of end-to-end deterministic communications, especially in industrial environments and time-critical applications like factory automation. We elaborate on the concepts of a TSN-aware Xhaul network, present a novel architecture, and describe a set of amendments required in order to enable network slicing. With the devised approach, a sliceaware TSN-enabled transport network can be controlled and managed in an end-to-end orchestrated way. Implementation experience and evaluation results are reported using TSN-enabled prototype devices, OpenAirInterface (OAI), and JOX slice orchestrator.

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Section: B Evaluationsupporting

confidence: 75%

Section: B Tsn For the Fronthaul-8021cm Profilementioning

confidence: 99%

Section: ) Disaggregated Ran Using Openairinterfacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Network Slicing for TSN-Based Transport Networks

et al. 2021

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“…Real-time systems are explicitly considered [36]. A significant portion of the research has been focused on implementations as part of wireless 5G [37].…”

Section: Time Sensitive Networkingmentioning

confidence: 99%

Invited Paper: Perishable Data in Smart Communities

Ricart

2020

2020 IEEE 28th International Conference on Network Protocols (ICNP)

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Distributed smart and connected community applications of the present and future will continuously sense perishable data on which they make decisions. We say the data are perishable when they represent information sensed at a past point in time, possibly at a distant part of the distributed application, and for which the ground truth could have since changed. This paper discusses actions the sensing source, the network, and the controller can take to make the best possible decisions given that we know only a delayed version of the truth. Some of these actions to preserve freshness of data are based on known real-time techniques such as Time Sensitive Networking. To these we add Information Theory applied on a message-by-message basis and cross-layer coordination between content and network handling. Both the unexpectedness (surprisal) and timeliness (freshness) properties of perishable information can be encoded using a Shannon information entropy framework. Examples of smart community systems of the future for which these concepts are relevant are given.

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On the Realization of Cloud-RAN on Mobile Edge Computing

Ocampo

Bryhni

2023

Advanced Information Networking and Applications

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Time-Sensitive Networking for 5G Fronthaul Networks

Cited by 19 publications

References 15 publications

Network Slicing for TSN-Based Transport Networks

Network Slicing for TSN-Based Transport Networks

Invited Paper: Perishable Data in Smart Communities

On the Realization of Cloud-RAN on Mobile Edge Computing

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