Congestion Control and Traffic Differentiation for Heterogeneous 6TiSCH Networks in IIoT

Area of Science:

• Computer Science
• Network Engineering
• Industrial Internet of Things

Background:

• The Routing Protocol for Low power and lossy networks (RPL) is standard for Industrial IoT (IIoT) but struggles with congestion and traffic prioritization in heterogeneous 6TiSCH networks.
• Heavy loads cause parent node congestion, degrading packet delivery and increasing delay.
• RPL lacks explicit strategies for differentiating traffic criticality.

Purpose of the Study:

• To introduce congestion control and service differentiation strategies for heterogeneous 6TiSCH networks in IIoT applications.
• To address performance degradation issues in RPL under heavy load scenarios.
• To improve network reliability and efficiency for critical industrial data.

Main Methods:

• Implemented a congestion control mechanism using queue backlog monitoring and sharing among neighbor nodes.
• Defined a new routing metric incorporating queue occupancy for parent node selection during congestion.
• Designed a multi-queue model for prioritized transmission of critical over non-critical data.

Main Results:

• The proposed strategies achieve effective load balancing under heavy traffic conditions.
• Improved packet delivery ratios and reduced queue losses were observed.
• Enhanced delay performance for critical traffic transmission was demonstrated through simulations.

Conclusions:

• The developed congestion control and service differentiation strategies significantly improve RPL performance in IIoT 6TiSCH networks.
• The approach effectively mitigates congestion and prioritizes critical data, enhancing overall network reliability.
• The findings support the adoption of these strategies for robust IIoT communication.