Target Wake Time Scheduling for Time-Sensitive Networking in the Industrial IoT

Time Sensitive Networking (TSN) is fundamental for the low-latency, reliable, and energy-efficient networks that will enable the Industrial Internet of Things (IIoT). Wi-Fi has historically been considered unfit for TSN, as channel contention and collisions prevent deterministic transmission delays. However, this issue can be overcome using Target Wake Time (TWT) to instruct Wi-Fi stations to wake up and transmit in non-overlapped TWT Service Periods (SPs) and sleep in the remaining time. In this paper, we first formulate the TWT Acceptance and Scheduling Problem (TASP), whose objective is to schedule TWT SPs as to maximize traffic throughput and energy efficiency while respecting Age of Information (AoI) constraints. Then, since the TASP is NP-hard, we propose the TASP Efficient Resolver (TASPER), a heuristic strategy to find near-optimal solutions efficiently. Finally, we compare TASPER with several baselines through numerical analysis and simulations, which we performed using a TWT-compatible simulator based on ns-3. We demonstrate that TASPER schedules traffic with up to 21.23% higher priority-weighted admission ratio and saves up to 7.42% energy compared to the ShortestFirst strategy, all while satisfying AoI constraints for 99.5% of transmissions.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/pimrc59610.2024.10817339
Primary Topic
Network Time Synchronization Technologies
Type
article
Field-Weighted Citation Impact
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article

Target Wake Time Scheduling for Time-Sensitive Networking in the Industrial IoT

Corrado Puligheddu, Francesco Raviglione, Carla Fabiana Chiasserini, Claudio Casetti et al.
Network Time Synchronization Technologies
article

Target Wake Time Scheduling for Time-Sensitive Networking in the Industrial IoT

Corrado Puligheddu, Francesco Raviglione, Carla Fabiana Chiasserini, Claudio Casetti, Riccardo Rusca, Fabio Busacca, Sergio Palazzo
article en

Abstract

Time Sensitive Networking (TSN) is fundamental for the low-latency, reliable, and energy-efficient networks that will enable the Industrial Internet of Things (IIoT). Wi-Fi has historically been considered unfit for TSN, as channel contention and collisions prevent deterministic transmission delays. However, this issue can be overcome using Target Wake Time (TWT) to instruct Wi-Fi stations to wake up and transmit in non-overlapped TWT Service Periods (SPs) and sleep in the remaining time. In this paper, we first formulate the TWT Acceptance and Scheduling Problem (TASP), whose objective is to schedule TWT SPs as to maximize traffic throughput and energy efficiency while respecting Age of Information (AoI) constraints. Then, since the TASP is NP-hard, we propose the TASP Efficient Resolver (TASPER), a heuristic strategy to find near-optimal solutions efficiently. Finally, we compare TASPER with several baselines through numerical analysis and simulations, which we performed using a TWT-compatible simulator based on ns-3. We demonstrate that TASPER schedules traffic with up to 21.23% higher priority-weighted admission ratio and saves up to 7.42% energy compared to the ShortestFirst strategy, all while satisfying AoI constraints for 99.5% of transmissions.

Politecnico di Torino (IT), University of Catania (IT)
European Commission
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
Network Time Synchronization Technologies
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