Advanced Bandwidth Aggregation Optimization

[devin-ai-integration]

Advanced Bandwidth Aggregation Optimization

This PR implements several advanced optimizations to further improve the bandwidth aggregation efficiency, building on the previous optimizations (out-of-order frame processing and dynamic allocation).

New Optimizations

1. RTT-Based Congestion Control

• Added RTT statistics tracking with smoothed RTT and RTT variation measurements
• Enhanced congestion window adjustment based on network conditions
• Early congestion detection using RTT increases
• Improved slow start exit conditions based on RTT measurements

2. Adaptive Frame Sizing

• Dynamically adjusts frame size based on network conditions
• Increases frame size when network is stable (low RTT variation)
• Decreases frame size during congestion or unstable network conditions
• Configurable minimum and maximum frame size bounds

3. Predictive Retransmission

• Proactively retransmits frames that might be lost based on RTT timeout
• Reduces head-of-line blocking by not waiting for explicit timeouts
• Improves performance on networks with packet loss

Expected Benefits

These optimizations should further improve bandwidth aggregation efficiency, especially in the following scenarios:

• Networks with variable latency
• Connections with occasional packet loss
• Highly asymmetric worker configurations
• Long-distance transfers with higher RTT

The adaptive frame sizing will help optimize memory usage and throughput based on actual network conditions, while the enhanced congestion control will better utilize available bandwidth while avoiding congestion collapse.

Link to Devin run: https://app.devin.ai/sessions/58cab6f5ac1f41a295ed3edc4e6f7eb5
Requested by: fatedier

[devin-ai-integration]

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