Fine-Grained Real-Time Flow Scheduling in Wireless TSCH Networks

• Xindan Liang,
• Ying Qiu,

Vol. 19, No. 7, July 31, 2025
10.3837/tiis.2025.07.013, Download Paper (Free):

• Event-Triggered Flows
• real-time scheduling
• Reduce Period
• Time-Triggered Flows
• Wireless Sensor-Actuator Networks

Abstract

With the advancement of Internet of Things technology, Wireless Sensor-Actuator Networks (WSANs) have been widely applied in industrial process monitoring and control. However, due to the susceptibility of wireless communication to electromagnetic interference in industrial environments, the real-time performance of the network is difficult to guarantee. Time-Slotted Channel Hopping (TSCH) is an essential method for ensuring real-time performance and has been widely studied. However, existing scheduling algorithms can only schedule certain specific time-triggered flows, and the granularity of time-triggered flows is relatively coarse. To address these issues, we have proposed a new centralized scheduling algorithm FGRTS, which utilizes the principle of prime factorization to reduce the periods of time-triggered flows, thereby reducing the superframe length of the network, decreasing the granularity of scheduling, and lowering sending delays. Additionally, we employ a combined reservation and preemption approach to schedule event-triggered flows, reserving suitable time slots for event-triggered flows while allowing for preemption of time slots for time-triggered flows in emergencies. In order to improve the adaptability of the FGRTS to large-scale networks, we utilize grouping to separate scheduling to avoid interference. The experimental results indicate that the FGRTS can reduce the superframe length by ten orders of magnitude. Under moderate traffic demands, the schedulability ratio of the FGRTS exceeds 80%, which is a 48% improvement compared to unreduced time-triggered flows. In large-scale networks with moderate traffic demand, the average slot utilization ratio of FGRTS is maintained at around 80%.

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