Dynamic Virtual Channel Allocation for Time-Sensitive Networking
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Solution Overview
Problem
Current computer communication systems face challenges in ensuring deterministic timing and low latency for time-sensitive applications over networks, particularly in scenarios like audio and video streaming, due to variations in data delivery delays and congestion on memory access buses.
Innovation Solution
A network manager dynamically allocates virtual channels over a time-sensitive networking bus, using predictive models and inference computations to prioritize and optimize resource allocation based on urgency levels and latency requirements, allowing for reallocation of resources to meet timing demands of computing tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If buffering is used to reduce data delivery failures, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent implements dynamic virtual channel allocation where the network manager continuously adjusts channel assignments based on real-time traffic patterns and latency requirements. This dynamic approach allows the system to adapt buffer sizes and allocation strategies to minimize both data loss and time delay, resolving the contradiction between reliability and time loss.
Solution Approach 2:
The system changes key parameters such as virtual channel priorities, bandwidth allocations, and buffer sizes based on predicted traffic patterns and current system state. By dynamically adjusting these parameters, the system achieves both reliable data delivery and minimal buffering delay.
2Device complexity
If virtual channel allocation is static, then device complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The network manager autonomously performs virtual channel allocation and reallocation based on predicted traffic patterns and system state. This self-service mechanism eliminates the need for complex manual configuration while maintaining high adaptability to changing timing requirements, resolving the contradiction between complexity and adaptability.
Solution Approach 2:
The system uses predictive models to forecast future traffic patterns and proactively adjusts virtual channel allocations before actual congestion or timing violations occur. This preliminary action allows the system to adapt to future requirements without increasing real-time complexity.
3Ease of operation
If resource allocation is fixed, then ease of operation is improved, but productivity deteriorates
Solution Approach 1:
The network manager continuously monitors system state, traffic patterns, and latency performance, then uses this feedback to dynamically optimize resource allocation. This feedback-driven approach maintains operational simplicity while significantly improving system throughput and productivity through automated optimization.
Solution Approach 2:
The patent replaces manual, mechanical resource allocation mechanisms with automated algorithms that use predictive modeling and machine learning. This substitution maintains ease of operation for users while dramatically improving system productivity through intelligent, data-driven decision-making.
4Reliability
If deterministic timing is enforced, then reliability is improved, but device complexity increases
Solution Approach 1:
The system dynamically adjusts virtual channel priorities and allocations in real-time to maintain deterministic timing guarantees even as traffic patterns change. This dynamic adaptation allows the system to achieve reliability without requiring overly complex static scheduling configurations.
Solution Approach 2:
The network manager uses predictive models to forecast future traffic and pre-adjust channel allocations to ensure deterministic timing will be maintained. This preliminary action simplifies real-time scheduling complexity by anticipating future requirements and preparing allocations in advance.
Data Source
AI summary
A computing system, having: a plurality of components operable to perform computing tasks; a plurality of memory devices operable to provide memory and storage services to the computing tasks; a network of physical connections configured between the components and the memory devices to form a bus for the computing tasks to access the memory and storage services; and a network manager configured to allocate virtual channels, through the bus, for the computing tasks to access the memory and storage services with deterministic timing.