Resource Usage Ratio Scheduling for Adaptive Wireless Streams
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Solution Overview
Problem
Existing resource allocation methods in wireless environments for industrial applications fail to adapt quickly and accurately to sudden changes in application performance requirements, leading to inefficiencies and potential failures in communication systems.
Innovation Solution
A method for computing and transmitting configuration-based resource usage ratios to guide resource schedulers, using a common time window to determine optimal allocation of radio resources based on application parameters, ensuring each stream is allocated in at least one configuration, and employing optimization techniques to minimize failure probability, power consumption, or maximize throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing resource allocation methods predict future allocations from past allocations, then resource allocation is simplified, but the system cannot adapt quickly to sudden changes in application performance requirements
Solution Approach 1:
The patent pre-calculates resource usage ratios for multiple possible configurations before they are needed. By computing these ratios in advance based on application parameters and transmitting them to the scheduler, the system准备好 adaptation capabilities ahead of time, enabling quick response to sudden changes without complex real-time calculations
Solution Approach 2:
The system dynamically adapts resource allocation by selecting from pre-computed configurations based on current conditions. The resource usage ratios are configured for different scenarios and can be switched dynamically without recalculating everything, balancing adaptability with computational efficiency
2Reliability
If TSN based networks provide deterministic latency guarantees, then reliability is improved, but flexibility to support mobile industrial applications is lost
Solution Approach 1:
The patent segments the resource allocation into discrete configurations, each optimized for specific conditions. This allows the system to maintain deterministic guarantees within each configuration while switching between configurations to support different mobile scenarios, thus preserving both reliability and flexibility
Solution Approach 2:
The system changes allocation parameters by selecting different pre-configured configurations rather than continuously adjusting them. This discrete parameter change approach maintains the deterministic nature of TSN while adapting to varying mobile application requirements
3Reliability
If TAS schedulers guarantee bounded ultra-low latency transmission, then communication reliability is improved, but overhead increases and performance degrades for short lived flows
Solution Approach 1:
The patent applies TAS scheduling selectively rather than uniformly to all traffic. By using pre-computed resource usage ratios to determine when and how to apply time-aware shaping, the system maintains deterministic guarantees only when necessary, reducing overhead for short-lived flows while preserving reliability for critical communications
Data Source
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AI summary
A method in a system comprising a resource scheduler and a set of devices is disclosed. Each device hosts at least one application, each application transmitting a stream of messages to at least one receiver. The method comprises : - obtaining (S 100), for each stream, parameters comprising one message lifetime, one message period and a last buffering time of a message of said stream before a given time window starts ; - deducing (S102) a set of configurations of said streams in said time window ; - computing (S 104), for each configuration, one configuration-based resource usage ratio per each stream ; - transmitting (S106) data to the resource scheduler, said data comprising each configuration with its computed set of configuration-based resource usage ratios.