Radio Resource Allocation Using Fairness and Failure Feedback
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Solution Overview
Problem
Current wireless communication systems in smart factories face challenges in providing reliable and flexible resource allocation for mobile industrial applications, as Time Sensitive Networking (TSN) suffers from high overhead for short-lived flows and lacks the flexibility needed for future factory environments, while wireless networks compromise reliability for ease of deployment.
Innovation Solution
A resource scheduler allocates radio resources using an α-fair utility-based formalism to balance application requirements, minimizing application failures and ensuring fair resource sharing among devices, by considering metrics such as resilience, message lifetime, and channel error probability, and updating application parameters to optimize communication performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If TSN is used to guarantee deterministic latency requirements, then reliability is improved, but device complexity and overhead increase
Solution Approach 1:
The patent changes the scheduling parameters from TSN's time-based deterministic scheduling to utility-based scheduling with adjustable weights. The scheduler uses application-specific parameters (importance weights, deadline preferences) to dynamically adjust resource allocation, maintaining reliability guarantees while reducing overhead through more efficient scheduling decisions.
Solution Approach 2:
The patent introduces dynamic scheduling where resource allocation adapts to changing application requirements. The scheduler continuously adjusts resource distribution based on current system state and application priorities, replacing static TSN configurations with flexible dynamic allocation that reduces overhead while maintaining performance guarantees.
2Ease of operation
If wireless networks are deployed for flexibility and ease of deployment, then ease of operation is improved, but reliability deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the scheduler continuously monitors channel conditions, application performance, and resource utilization. This feedback loop enables the system to adapt to wireless channel variations and maintain reliable communication by adjusting resource allocation in response to real-time conditions, thus preserving reliability while using flexible wireless networks.
Solution Approach 2:
The patent performs preliminary actions by pre-configuring application parameters and importance weights before resource allocation. The system prepares scheduling decisions in advance based on predicted requirements, allowing it to respond quickly to wireless conditions while maintaining reliability through pre-planned resource reservation for critical applications.
3Productivity
If resource allocation optimizes for application requirements, then productivity is improved, but fairness among devices deteriorates
Solution Approach 1:
The patent introduces asymmetric resource allocation where different devices receive different resource shares based on their application requirements and importance weights. The scheduler deliberately creates asymmetric allocation patterns to optimize overall system productivity while using fairness constraints to prevent complete starvation of lower-priority devices, thus balancing productivity and fairness.
Solution Approach 2:
The patent uses adjustable parameters (importance weights, minimum resource guarantees, maximum allocations) to control the trade-off between productivity optimization and fairness. By dynamically changing these parameters based on system state and application priorities, the scheduler can shift between more productivity-oriented and more fairness-oriented allocation modes.
Data Source
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AI summary
A method for allocating a radio resource in a system comprising a resource scheduler and a set of devices is disclosed. Each device hosts at least one application, each application transmitting messages to at least one receiver on a transmission channel. The resource scheduler first receives (S40), from each application, application parameters representative of application's requirements. Then, it computes (S42), for each application, a metric responsive to at least part of the received application parameters, to an average probability of failure of said application and further to a channel error probability of said transmission channel. The metrics are compared (S44) and, responsive to said comparison, it selects the application to allocate the radio resource to. The average probability of failure each application is further updated (S46). Finally, it transmits (S48) an instantaneous probability of failure to each application, said instantaneous probability of failure being used by said application to update its application parameters.