AI Pacing Engine for Data Communication Congestion
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Solution Overview
Problem
Data communication devices, such as smart NICs, face congestion and performance degradation due to inefficient pacing of content transfer requests in storage sub-systems, leading to bottlenecks in cache and peripheral interfaces, which are exacerbated by varying hardware configurations and traffic patterns.
Innovation Solution
A data communication apparatus equipped with an artificial intelligence model that simulates and predicts storage sub-system states and pacing metrics, optimizing pacing actions such as adjusting pacing periods and cache sizes to maximize performance parameters like bandwidth and cache usage, trained using reinforcement learning and log data from the storage sub-system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional pacing methods are used in storage sub-systems, then device complexity is reduced, but performance degradation and congestion occur due to inefficient pacing of content transfer requests
Solution Approach 1:
The patent creates a digital twin (simulation engine) that copies the behavior and state of the physical storage sub-system. This digital twin is trained using reinforcement learning to replicate the complex interactions between caching layers, storage devices, and traffic patterns, allowing the AI model to learn optimal pacing strategies without directly complicating the physical system architecture.
Solution Approach 2:
The patent replaces traditional rule-based pacing mechanisms with an AI-driven system. Instead of using fixed algorithms or manual configuration for pacing content transfer requests, the system employs a trained neural network that dynamically adjusts pacing parameters based on learned patterns from the digital twin simulation, substituting mechanical control logic with intelligent decision-making.
2Productivity
If pacing parameters are dynamically adjusted to optimize performance, then data throughput improves, but the difficulty of detecting and measuring system states increases
Solution Approach 1:
The patent introduces a digital twin as an intermediary between the physical storage sub-system and the AI pacing controller. The digital twin receives and processes system state data (cache states, storage device status, traffic patterns) and presents processed information to the AI model, simplifying the measurement and detection complexity while enabling sophisticated performance optimization.
3Adaptability or versatility
If reinforcement learning is used to train the AI model, then adaptability to varying traffic patterns improves, but loss of time during model training occurs
Solution Approach 1:
The patent performs preliminary training of the AI model offline using a digital twin that simulates various traffic patterns and workloads. By pre-training the model with diverse scenarios before deployment, the system achieves high adaptability to varying traffic patterns without incurring training time delays during actual operation. The digital twin allows extensive training to occur in advance, preparing the model for real-time deployment.
4Ease of operation
If AI model predicts future states to optimize pacing, then system responsiveness improves, but manufacturing precision of timing control deteriorates due to predictive uncertainty
Solution Approach 1:
The patent employs a dynamic pacing strategy where the AI model continuously adjusts pacing parameters based on predicted future states and actual system feedback. Rather than relying on static timing schedules, the system adapts pacing intervals and rates dynamically, allowing it to respond to changing conditions while managing predictive uncertainty through continuous learning and adjustment.
Data Source
AI summary
In one embodiment, a processing apparatus includes a processor to train an artificial intelligence model as data communication apparatus simulation engine to simulate operation of data communication apparatus, responsively to training data derived from log data collected about the data communication apparatus