DPU-GPU Packet Digest for Adaptive Network Policy

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Solution Overview

Problem

Existing network communication systems face challenges in dynamically managing and monitoring data traffic due to varying traffic patterns, noise, and non-uniform accuracy, which existing software solutions struggle to scale effectively for preventive maintenance and security.

Innovation Solution

A system combining a data processing unit (DPU) and a graphical processing unit (GPU) processes network packets, derives a packet digest through metadata extraction and data reduction, and applies machine learning algorithms to adapt policies dynamically, enabling continuous matching of policies to current traffic characteristics.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If software solutions are used for network traffic monitoring and management, then basic policy enforcement is possible, but scalability and performance deteriorate under varying traffic patterns

Engineering Contradiction:
Improvenetwork traffic processing throughputVSAvoidsoftware solution complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The system segments network traffic processing into multiple independent streams handled by parallel workers, where each worker processes a subset of traffic patterns. This allows the system to scale horizontally by adding more workers without increasing the complexity of individual processing units, thereby maintaining high throughput while managing complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces a new dimension of processing by implementing multi-level policy hierarchies and multi-stage processing pipelines. Traffic is processed through multiple layers of policy evaluation (e.g., L3 policies, L4 policies, application-layer policies) rather than a single flat layer, enabling complex traffic management without proportionally increasing the complexity of any single processing component.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If traditional processing systems are used, then implementation is straightforward, but adaptability to changing traffic patterns and security threats deteriorates

Engineering Contradiction:
Improvepolicy adaptability to traffic patternsVSAvoidsystem architecture complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements dynamic policy adaptation where policy rules can be modified in response to changing traffic patterns and security threats. The multi-level policy hierarchy allows different policy layers to be independently updated without reconfiguring the entire system, enabling adaptability while controlling complexity through modular policy management.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback mechanisms where traffic analysis results from lower-level policies inform higher-level policy decisions. This multi-stage feedback loop enables the system to adapt to changing conditions by continuously learning from processed traffic data and adjusting policy enforcement accordingly, maintaining adaptability without requiring complete system redesign.

Inventive Principle:
Principle #23Feedback

3Measurement precision

If comprehensive packet analysis is performed, then security and QoS monitoring accuracy improves, but processing time and resource consumption increase

Engineering Contradiction:
Improvetraffic pattern detection accuracyVSAvoidpacket processing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system applies partial analysis by evaluating only the necessary policy layers for each traffic packet based on its characteristics. Not all packets require full multi-level inspection - the system performs selective deep packet analysis only when needed, while applying lighter inspection to routine traffic, thereby maintaining high detection accuracy for critical threats while reducing average processing time.

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The multi-level policy hierarchy performs preliminary filtering at lower layers (L3, L4) before advancing to more intensive application-layer analysis. This staged approach allows the system to quickly identify and handle routine traffic with minimal processing, while reserving comprehensive analysis only for packets that require deeper inspection, thus improving overall processing efficiency without sacrificing detection accuracy.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS11374838B1Using a data processing unit (DPU) as a pre-processor for graphics processing unit (GPU) based machine learning
Publication Date: 2022.06.28 MELLANOX TECHNOLOGIES LTD(IL)
  • US11374838B1 patent drawing
  • US11374838B1 patent drawing

AI summary

A system includes a network adapter and a processor. The network adapter is configured to receive packets from a network, to process the received packets in accordance with a policy, and to derive a packet digest from the received packets. The processor is configured to adapt the policy based on the packet digest derived by the network adapter, and to provide the adapted policy to the network adapter for subsequent packet processing.