Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications

Industry 4.0 has transformed manufacturing and automation by integrating cyber–physical systems with the Industrial Internet of Things (IIoT) for real-time monitoring, intelligent control, and data-driven decision making. The IIoT increasingly relies on IEEE 802.15.4e Time-Slotted Channel Hopping (T...

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Main Authors: Nilam Pradhan, Bharat S. Chaudhari, Prasad D. Khandekar
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Telecom
Subjects:
Online Access:https://www.mdpi.com/2673-4001/6/2/41
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author Nilam Pradhan
Bharat S. Chaudhari
Prasad D. Khandekar
author_facet Nilam Pradhan
Bharat S. Chaudhari
Prasad D. Khandekar
author_sort Nilam Pradhan
collection DOAJ
description Industry 4.0 has transformed manufacturing and automation by integrating cyber–physical systems with the Industrial Internet of Things (IIoT) for real-time monitoring, intelligent control, and data-driven decision making. The IIoT increasingly relies on IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) to achieve reliable, low-latency, and energy-efficient industrial communications. The 6TiSCH protocol stack integrates scheduling and routing to optimize transmissions for resource-constrained devices, enhancing Quality of Service (QoS) in IIoT deployments. This paper proposes an innovative adaptive and cross-layer slotframe allocation technique for 6TiSCH networks, dynamically scheduling cells based on node hop distance, queue backlog, predicted traffic load, and link quality metrics. By dynamically adapting to these parameters, the proposed method significantly improves key QoS metrics, including end-to-end latency, packet delivery ratio, and network lifetime. The mechanism integrates real-time queue backlog monitoring, link performance analysis, and energy harvesting awareness to optimize cell scheduling decisions proactively. The results demonstrate that the proposed strategy reduces end-to-end latency by up to 32%, enhances PDR by up to 27%, and extends network lifetime by up to 10% compared to state-of-the-art adaptive scheduling solutions.
format Article
id doaj-art-41d90735510a4847bf5418e8d08afc6a
institution Kabale University
issn 2673-4001
language English
publishDate 2025-06-01
publisher MDPI AG
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series Telecom
spelling doaj-art-41d90735510a4847bf5418e8d08afc6a2025-08-20T03:27:26ZengMDPI AGTelecom2673-40012025-06-01624110.3390/telecom6020041Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT ApplicationsNilam Pradhan0Bharat S. Chaudhari1Prasad D. Khandekar2Department of Electrical and Electronics Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune 411038, IndiaDepartment of Electrical and Electronics Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune 411038, IndiaDepartment of Electrical and Electronics Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune 411038, IndiaIndustry 4.0 has transformed manufacturing and automation by integrating cyber–physical systems with the Industrial Internet of Things (IIoT) for real-time monitoring, intelligent control, and data-driven decision making. The IIoT increasingly relies on IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) to achieve reliable, low-latency, and energy-efficient industrial communications. The 6TiSCH protocol stack integrates scheduling and routing to optimize transmissions for resource-constrained devices, enhancing Quality of Service (QoS) in IIoT deployments. This paper proposes an innovative adaptive and cross-layer slotframe allocation technique for 6TiSCH networks, dynamically scheduling cells based on node hop distance, queue backlog, predicted traffic load, and link quality metrics. By dynamically adapting to these parameters, the proposed method significantly improves key QoS metrics, including end-to-end latency, packet delivery ratio, and network lifetime. The mechanism integrates real-time queue backlog monitoring, link performance analysis, and energy harvesting awareness to optimize cell scheduling decisions proactively. The results demonstrate that the proposed strategy reduces end-to-end latency by up to 32%, enhances PDR by up to 27%, and extends network lifetime by up to 10% compared to state-of-the-art adaptive scheduling solutions.https://www.mdpi.com/2673-4001/6/2/416TiSCHautonomousadaptivescheduling techniqueIIoTlatency
spellingShingle Nilam Pradhan
Bharat S. Chaudhari
Prasad D. Khandekar
Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
Telecom
6TiSCH
autonomous
adaptive
scheduling technique
IIoT
latency
title Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
title_full Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
title_fullStr Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
title_full_unstemmed Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
title_short Adaptive Slotframe Allocation with QoS and Energy Optimization in 6TiSCH for Industrial IoT Applications
title_sort adaptive slotframe allocation with qos and energy optimization in 6tisch for industrial iot applications
topic 6TiSCH
autonomous
adaptive
scheduling technique
IIoT
latency
url https://www.mdpi.com/2673-4001/6/2/41
work_keys_str_mv AT nilampradhan adaptiveslotframeallocationwithqosandenergyoptimizationin6tischforindustrialiotapplications
AT bharatschaudhari adaptiveslotframeallocationwithqosandenergyoptimizationin6tischforindustrialiotapplications
AT prasaddkhandekar adaptiveslotframeallocationwithqosandenergyoptimizationin6tischforindustrialiotapplications