Research Area:  Internet of Things

Abstract:

The Industrial Internet of Things (IIoT) plays a vital role in Industry 4.0, thanks to advanced wireless protocols like IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) and their incorporation in the IPv6 stack via 6TiSCH. These protocols rely on carefully constructed schedules generated by a Scheduling Function (SF). The Minimal Scheduling Function (MSF) serves as the standard SF established by the 6TiSCH WG, prescribing the management and adaptation of the communication schedule based on traffic patterns. However, MSF has a notable drawback in adapting to traffic variability and burstiness and fails to account for link quality when updating TSCH cells. To address these limitations, this paper introduces the Hybrid Proactive Scheduler with Adaptive Channel Selection (HPS). HPS calculates cell requirements by considering resource utilization, ETX (Expected Transmission Count), and buffer allocation. It incorporates a fast response mechanism for burst traffic, implemented through an autonomous scheduling mechanism. Additionally, HPS utilizes a whitelisting mechanism to select optimal communication channels. The proposed scheme is implemented in Contiki-ng and evaluated in both simulated environments and real-world testbed. Obtained results demonstrate the potential of HPS to significantly enhance reliability and reduce delays compared to state-of-the-art SFs. Specifically, HPS consistently demonstrates reliability levels surpassing 90% across diverse scenarios accompanied with a noticeable gain in latency and power consumption of approximately 70% and 25%, respectively. These findings highlight the effectiveness of HPS in improving network performance and addressing the limitations of existing SFs.

Keywords:  

Author(s) Name:  Abdeldjalil Tabouche , Badis Djamaa , Mustapha Reda Senouci

Publisher name:  ScienceDirect

DOI:  10.1016/j.adhoc.2024.103527

Volume Information:  Volume 161, (2024)

Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S1570870524001380