Scalable Packet Analyzer Parallel Microengine Arrays
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Solution Overview
Problem
Existing packet analyzers face challenges in scaling to small size with low power and low latency while maintaining high throughput and cost-effectiveness, particularly in secure high-assurance communications, where real-time analysis and customization are required.
Innovation Solution
A scalable packet analyzer with a parallel hardware architecture using policy engine arrays and packet analysis microengines that can dynamically allocate resources and apply policy algorithms for parallel analysis and manipulation of data packets, incorporating redundancy for high assurance operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software intensive packet analyzers are used to achieve scalability, then adaptability is improved, but throughput rate and latency performance deteriorate
Solution Approach 1:
The packet analyzer is divided into multiple policy engine arrays, each containing multiple packet analysis microengines. This segmentation allows the system to process packets in parallel across multiple hardware units, achieving both high throughput and adaptability. Each microengine can be independently configured with different policy algorithms, enabling scalable customization without sacrificing performance.
Solution Approach 2:
The patent transitions from software-based packet analysis to a hardware-based parallel processing architecture. By moving the analysis function from a single software thread to multiple concurrent hardware microengines operating in parallel, the system achieves dimensional expansion in processing capacity, simultaneously improving throughput and maintaining adaptability through configurable policy algorithms.
2Productivity
If processing resources are increased to improve throughput, then productivity is improved, but device complexity and cost increase non-linearly
Solution Approach 1:
The system segments packet analysis into discrete, independent microengine units organized in arrays. Each microengine is a standardized module that can be replicated and configured independently. This modular segmentation allows linear scaling of throughput by adding more microengines without proportionally increasing overall system complexity, as each unit follows the same architectural template.
Solution Approach 2:
The patent implements dynamic resource allocation where the number of active policy engine arrays and microengines can be adjusted based on throughput requirements. The system can dynamically activate or deactivate microengines and reconfigure policy algorithms, allowing flexible adaptation to different traffic loads without requiring a fixed complex architecture for maximum capacity.
3Productivity
If more packet analysis microengines are allocated to meet higher throughput requirements, then productivity is improved, but use of energy and device size increase
Solution Approach 1:
The system employs dynamic resource allocation where packet analysis microengines can be activated or deactivated based on real-time throughput requirements. When traffic load is low, fewer microengines are active, reducing power consumption. When throughput demands increase, additional microengines are activated to meet the required data processing capacity, optimizing the energy-performance tradeoff.
Solution Approach 2:
The patent implements a resource management mechanism where unused or underutilized microengine capacity can be deactivated to conserve energy, and the same hardware resources can be recovered and reactivated when throughput requirements increase. This allows the system to discard computational resources during low-load periods and recover them when needed, rather than continuously consuming power at maximum capacity.
4Reliability
If redundancy is implemented for high assurance operation, then reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent implements redundancy through segmented parallel processing where multiple policy engine arrays and microengines can operate simultaneously on the same or different packets. This segmentation-based redundancy provides high assurance operation by enabling cross-validation of packet analysis results across multiple independent processing paths, while maintaining manageable complexity through modular, replicated units rather than monolithic redundant systems.
Data Source
AI summary
A scalable packet analyzer receives data packets from a data packet source for packet analysis and includes a plurality of policy engine arrays, each having a plurality of packet analysis microengines. A policy algorithm loader module is operative with each packet analysis microengine for loading a policy algorithm to each packet analysis microengine such that each packet analysis microengine analyzes specific sections of the data packet in parallel within each policy engine array based on the applied policy algorithm to obtain data about the data packet for further data packet processing.