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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MDPI AG
2025-06-01
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| Series: | Telecom |
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| 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 |
| record_format | Article |
| 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 |
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