Problem

Existing network testing systems face a critical limitation in handling high-volume test data from devices under test (DUTs). Current approaches can only store "end-of-test" results in relational databases, discarding valuable real-time data collected during testing, which severely limits post-test analysis capabilities. The core challenge is that data streams from different sources arrive asynchronously with imperfectly synchronized time bases, making it difficult to correlate control-plane statistics, data-plane statistics, and configuration data using traditional timestamp matching approaches. When testing equipment fails due to transient errors, engineers cannot drill down into specific time ranges to understand root causes because the real-time correlation data was never preserved.

Solution

A time-interval-based correlation system that captures and stores both real-time and end-of-test results in a unified queryable database using an OLAP-style star schema architecture. Instead of relying on exact timestamp matching, the system specifies recording time intervals of fifteen seconds or less, allowing data from multiple asynchronous sources with different time bases to be correlated within the same interval boundaries. The solution persists counter values and statistics from numerous data streams (70 or more) during high-volume testing, creating time series data that can handle counters with various resolutions and time bases. At test conclusion, the system correlates the recorded time series data with test configuration data and external sources using correlation intervals that are greater than or equal to the specified recording intervals. This approach enables seamless correlation of control-plane statistics, data-plane statistics, learned values, and configuration parameters for comprehensive post-test analysis. The architecture makes no fundamental distinction between real-time and end-of-test results, storing both types in fact tables with shared dimension attributes that enable complex analytical queries.

Key Features

Based on what we learned about your invention from the interview, our Discovery Agent performed a real-time and confidential prior art search using a proprietary database of millions of U.S. and foreign patents, as well as non-patent literature. The Discovery Agent analyzed the most relevant documents to provide the key patentability insights below. Your invention operates in the network testing and test data management domain, specifically addressing how high-volume telemetry from devices under test can be captured, correlated, and analyzed when data arrives asynchronously from multiple sources.

The most distinctive aspects of your approach appear to center on architectural choices rather than the correlation technique itself. What stands out in this landscape includes:

• The unified storage architecture that treats real-time streaming data and end-of-test results identically using star schema fact tables, eliminating separate processing paths that characterize traditional test data systems
• The high-volume counter persistence system that maintains instances of 70+ simultaneous counter values at sub-15-second intervals, preserving temporal granularity across heterogeneous data streams with different resolutions
• The combination of OLAP-style analytics with network test data management, enabling complex post-test queries across control-plane statistics, data-plane statistics, and configuration parameters within the same database structure

The prior art landscape shows established techniques for time-interval-based correlation of asynchronous data. US6453359B1 explicitly discloses grouping data from multiple systems with imperfectly synchronized time bases into common time intervals using tolerance-based assignment, directly addressing the timestamp matching challenge you identified. Similarly, US2014003454A1 describes coordinating data from sources with unsynchronized clocks using interval-based synchronization markers. These patents demonstrate that the core correlation mechanism—using time intervals rather than exact timestamps to align asynchronous data—has been disclosed in other contexts.

The international patent landscape further confirms these established correlation and testing techniques. European patent EP2514125B1 addresses synchronization network configuration for time and frequency synchronization in hybrid networks combining physical and packet-based timing protocols, demonstrating recognition of time-alignment challenges in distributed systems. International application WO1999052234A1 discloses a unified testing system for communications networks that coordinates multiple test devices through a metacontroller architecture. The technical literature also establishes foundations in this space: the IEEE 1588-2008 Standard provides protocols for precision clock synchronization in networked measurement and control systems, while academic work such as Deri et al.'s research on compressed time-series databases for real-time monitoring data (Traffic Monitoring and Analysis, Springer 2012) demonstrates established approaches to storing high-volume time-stamped data streams.

However, the search revealed no prior art combining this correlation approach with your specific architectural innovations for network testing. The star schema storage model that seamlessly handles both real-time and end-of-test data without architectural distinction appears to be less commonly disclosed. The persistence of high-volume counter streams (70+ sources) at such fine temporal resolution within a unified queryable structure also appears distinctive in this domain.

Your strategic opportunities likely center on the architectural integration and implementation specifics rather than the correlation principle alone. The combination of interval-based correlation with OLAP-style analytics for network test data, the specific handling of heterogeneous counter resolutions, and the unified treatment of streaming versus final results may offer differentiation paths. During patent preparation and prosecution, emphasizing how these elements work together to solve the specific challenges of network test data management—particularly the ability to drill down into transient failures using preserved real-time correlation data—could strengthen your position. A Landfall IP patent attorney can help identify the strongest strategic positioning for your specific approach, especially around the architectural choices that enable post-test analysis capabilities not previously available in network testing systems.

Research across thousands of U.S. startups have demonstrated the value of patents for early-stage companies.

• Funding advantage: Startups with patents are 6–10x more likely to secure VC and raise larger rounds [1][2][4].
• Valuation premium: Patent-holding startups achieve 50–90% higher valuations at key funding stages [3].
• Growth & exit success: Patented startups see faster revenue and job growth, and are twice as likely to exit at premium prices [1][3][4].
• Strategic leverage: Patents enable licensing revenue, attract enterprise partners, and create defensible market positions [3].

Ready to make Landfall? Schedule a free consultation to review your report and discuss how to protect your idea.