Multi-flow Compression for Network Congestion Reduction
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Solution Overview
Problem
Network congestion in data communication networks is not effectively addressed by existing congestion control techniques, which often rely on hardware optimization and flow control mechanisms, and there is a need for a more efficient method to manage traffic and reduce latency.
Innovation Solution
A device and system that utilize a data compression engine to compress similar data packets from multiple network flows into compressed packets, which are then sent over the network, and a decompression engine to decompress these packets at their destination, thereby reducing network load and increasing throughput by exploiting redundancy between flows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional congestion control techniques are used, then network stability is maintained, but network throughput is not optimized and latency is high
Solution Approach 1:
The patent merges multiple similar packets from different network flows into a single compressed packet. The compression engine identifies packets with similar payloads across multiple flows and combines them, transmitting only one compressed packet instead of multiple identical packets, thereby reducing network traffic volume and improving throughput while lowering latency
Solution Approach 2:
The compression engine performs multiple functions: it monitors multiple network flows simultaneously, identifies similarity patterns across different flows, compresses the data, and manages decompression at the destination. This multi-functional approach optimizes network traffic handling comprehensively
2Productivity
If data compression is applied to multiple network flows, then network load is reduced and throughput increases, but device complexity increases
Solution Approach 1:
The compression engine automatically monitors incoming packets from multiple flows, identifies similarity patterns, and performs compression without external intervention. The system self-manages the entire compression and decompression process, reducing the need for complex external control mechanisms
Solution Approach 2:
The patent changes the parameter of packet representation by transforming multiple similar packets into a single compressed packet with reduced data volume. This parameter change from full packets to compressed representations reduces network load while the compression engine handles the complexity of transformation
3Quantity of substance
If packets from multiple flows are compressed together, then network congestion is reduced, but packet order and integrity must be maintained
Solution Approach 1:
The patent segments the compression process by maintaining separate compression contexts for different flows while identifying similarity within payloads. The decompression engine segments the received compressed packets and reconstructs them in the correct order, ensuring packet integrity is maintained despite compression of multiple flows
Solution Approach 2:
The system implements feedback mechanisms where the compression engine monitors packet similarity and the decompression engine verifies packet reconstruction. This feedback ensures that compressed packets are properly decompressed and delivered in the correct order, maintaining integrity while reducing traffic volume
Data Source
AI summary
In one embodiment, a device includes a data compression engine configured to process data packets of multiple network flows received from a network, and compress respective groups of the received data packets into respective compressed packets for sending over the network, each respective compressed packet including respective ones of the received data packets from different ones of the network flows, wherein the network interface is configured to send the compressed packets over the network.