Dynamic TSN Flow Scheduling for QoS Adaptation
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Solution Overview
Problem
Current methods for configuring IEEE 802.1 Qbv in Time-Sensitive Networking (TSN) networks are complex and lack efficient algorithms for dynamic, on-line scheduling of flows, leading to increased latency and disruption in industrial communication systems, especially in scenarios with unknown or changing network flows.
Innovation Solution
A method for dynamically reconfiguring the schedule of flow transmissions in TSN networks by allocating time slots based on a fixed cycle duration, reducing the complexity of generating Gate Control Lists (GCLs) and allowing quick acceptance or rejection of new flows without compromising existing QoS, using a centralized or distributed approach to manage time resources across access switches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a predefined transmission schedule is used in TSN networks, then quality of service and latency are guaranteed, but the system lacks adaptability to changing network flows and requires complex reconfiguration
Solution Approach 1:
The patent implements dynamic scheduling by allowing the transmission schedule to be modified in real-time based on network conditions and new flow requirements. The system transitions from static predefined schedules to dynamic adaptive schedules that can accommodate changing traffic patterns while maintaining QoS guarantees through controlled reconfiguration mechanisms.
Solution Approach 2:
The system changes scheduling parameters dynamically by adjusting time slot allocations, cycle durations, and gate control list configurations based on observed network conditions. This allows the schedule to adapt to new flows and changing traffic patterns while maintaining deterministic behavior through parameter optimization.
2Measurement precision
If complex algorithms are used for dynamic scheduling, then flow acceptance decisions are accurate, but execution time and latency increase
Solution Approach 1:
The scheduling algorithm is segmented into multiple evaluation stages: initial quick assessment of flow requirements, intermediate resource availability checking, and final detailed scheduling validation. This hierarchical approach allows accurate flow acceptance decisions while minimizing execution time by eliminating unnecessary computations for flows that fail early criteria.
Solution Approach 2:
The system performs partial scheduling validation by checking only the most critical QoS parameters and resource constraints initially, rather than进行全面 validation. This allows fast rejection of incompatible flows while maintaining accurate acceptance decisions for promising candidates through subsequent detailed evaluation.
3Productivity
If time slots are allocated dynamically to access switches, then resource utilization improves, but scheduling complexity increases
Solution Approach 1:
The patent introduces a centralized scheduler or controller as an intermediary that manages time slot allocations across multiple access switches. This intermediary consolidates the scheduling complexity in a single entity while providing simplified interfaces to individual switches, enabling dynamic resource allocation without increasing complexity at each switch location.
Solution Approach 2:
The scheduling system implements universal time slot allocation mechanisms that can be applied across different access switches and flow types through standardized procedures. This multi-functional approach allows the same scheduling logic to handle diverse traffic patterns and switch configurations, improving resource utilization while avoiding the need for switch-specific complex algorithms.
Data Source
AI summary
A fast and dynamic configuration method for scheduling the transmission of flows in deterministic networks is provided. This method allows, when a new flow appears within the network, a decision to be made concerning a new schedule for transmitting flows, and allows it to be deployed in the network so as to assume this new flow without compromising the QoS of the other flows already present in the network.