Poster: Emergency-Aware TSCH Scheduling for High-Density Low-Power and Lossy Networks

High-density Low-Power Lossy Networks (LLNs) for IoT applications (e.g., smart cities) require ultra-low latency during emergencies like fires. Current TSCH schedulers (Orchestra, OST) use static/hash-based allocation, causing high delays and collisions for urgent traffic due to lack of prioritization and conflict resolution. In this paper, we present ETS, an emergencyaware scheduler featuring: (1) Binary-tree resource partitioning with preemption, (2) Slot-segmented RTS/CTS conflict avoidance, and (3) Multi-sink load balancing. Evaluations show ETS reduces latency by 23-42%, maintains 95% PDR, and lowers duty cycle by 37−52% versus baselines.

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Publication Details

Published
2025-08-20
DOI
https://doi.org/10.1109/rtcsa66114.2025.00034
Primary Topic
earthquake and tectonic studies
Type
article
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article

Poster: Emergency-Aware TSCH Scheduling for High-Density Low-Power and Lossy Networks

earthquake and tectonic studies
article

Poster: Emergency-Aware TSCH Scheduling for High-Density Low-Power and Lossy Networks

article en

Abstract

High-density Low-Power Lossy Networks (LLNs) for IoT applications (e.g., smart cities) require ultra-low latency during emergencies like fires. Current TSCH schedulers (Orchestra, OST) use static/hash-based allocation, causing high delays and collisions for urgent traffic due to lack of prioritization and conflict resolution. In this paper, we present ETS, an emergencyaware scheduler featuring: (1) Binary-tree resource partitioning with preemption, (2) Slot-segmented RTS/CTS conflict avoidance, and (3) Multi-sink load balancing. Evaluations show ETS reduces latency by 23-42%, maintains 95% PDR, and lowers duty cycle by 37−52% versus baselines.

Zhejiang University (CN)
Affordable and clean energy
Openalex Percentile: Top 41%
earthquake and tectonic studies
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Poster: Emergency-Aware TSCH Scheduling for High-Density Low-Power and Lossy Networks · (2025) | TGRS Research Map | TGRS