Network Traffic Transaction Analysis Using Thread Identifiers
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Solution Overview
Problem
Current network performance monitoring techniques lack real-time health information and semantic understanding of data streams, making it difficult to identify the source and cause of application issues, and often result in lost packet trace information and the need for application-specific code.
Innovation Solution
The method involves analyzing network traffic transactions by identifying thread identifiers, associating them with events, and generating temporal performance data to provide real-time health information, using techniques such as deep packet inspection and protocol-specific parsing to aggregate and filter network traffic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If deep packet inspection is performed to collect statistical information, then measurement precision of network traffic is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent segments network traffic monitoring into distinct functional modules: packet capture module, protocol parsing module, transaction identification module, and performance data generation module. Each module handles specific aspects of traffic analysis, reducing overall system complexity while maintaining measurement precision through specialized processing at each stage.
Solution Approach 2:
The patent introduces thread identifiers as intermediary elements that link packets to transactions without requiring deep inspection of packet contents. These identifiers act as mediators that connect network traffic data with application-level transactions, simplifying the monitoring process while preserving analytical precision.
2Measurement precision
If packet trace information is collected in detail, then measurement precision is improved, but loss of information occurs due to data volume and processing limitations
Solution Approach 1:
The patent extracts only the essential identifying features from packets (thread identifiers, transaction types, timing information) rather than collecting complete packet traces. This extraction approach maintains the ability to track and analyze transactions while significantly reducing data volume and preventing information loss due to processing limitations.
Solution Approach 2:
The patent performs preliminary tagging of packets with transaction identifiers at the point of capture. This preliminary action ensures that trace information is preserved in a condensed format from the outset, preventing information loss before processing begins and enabling efficient subsequent analysis without requiring storage of complete packet data.
3Measurement precision
If application-specific code is implemented for monitoring, then measurement precision for specific applications is improved, but adaptability to different applications decreases
Solution Approach 1:
The patent implements a universal monitoring framework that uses protocol-agnostic thread identifiers and transaction type classification. This universal approach allows the same monitoring infrastructure to accurately track multiple different applications and protocols without requiring application-specific code, thereby maintaining both precision and adaptability across diverse network traffic.
4Productivity
If real-time health information is provided, then productivity of monitoring is improved, but use of energy and processing resources increases
Solution Approach 1:
The patent performs partial monitoring by focusing only on extracting and tracking essential transaction identifiers and timing information rather than analyzing complete packet contents in real-time. This partial action approach enables real-time health information provision while significantly reducing processing resource consumption compared to full packet inspection.
Data Source
AI summary
Provided are methods and computer program products for analyzing and tracing the contents of network traffic in a network device and to help identify network performance issues. Methods for analyzing traffic include identifying thread identifiers associated with transactions, determining related events, and associating similar transactions and events into an aggregated list of transactions. Methods of tracing transactions include identifying thread identifiers associated with transactions and related events and serializing events into a serialized list of events to facilitate tracing single transactions.