Graph-Based Message Analytics for Real-Time Overlay Performance
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Solution Overview
Problem
Traditional message analysis systems are inefficient due to network dependency, outdated analytics information, and lack of real-time processing, leading to delays and inefficiencies in optimizing system performance.
Innovation Solution
Implementing an executable graph-based model with hypergraphs and overlay nodes for real-time message analysis, allowing instantaneous analytics generation and eliminating network dependency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a separate analytics system is used to analyze messages, then analytics information can be generated, but the analytics information becomes outdated before implementation and network dependency causes delays
Solution Approach 1:
The patent merges the analytics system with the native system by integrating the graph-based model directly into the system architecture. This allows the analytics engine to process messages in real-time within the same system that generates them, eliminating the separate analytics system and its associated network dependency delays. The graph model is embedded as a core component that continuously processes messages as they are generated.
Solution Approach 2:
The patent implements continuous real-time processing of messages through the graph-based model. Instead of batch processing or periodic analysis, the system continuously analyzes messages as they are generated and communicated, ensuring analytics information is always current. This continuous action eliminates the gap between message generation and analytics availability.
2Device complexity
If messages are communicated from native system to analytics system over network, then centralized analysis can be performed, but network availability becomes a bottleneck for real-time processing
Solution Approach 1:
The patent segments the analytics functionality into distributed graph-based models that can operate independently within the native system. Rather than requiring all messages to be sent to a centralized analytics system over the network, the graph model processes messages locally, eliminating network dependency and enabling faster processing while maintaining analytical capabilities.
3Loss of information
If traditional analytics system is used, then message analysis can be performed, but productivity is reduced due to waiting for analytics information
Solution Approach 1:
The patent implements preliminary action by having the graph-based model continuously process and analyze messages in real-time, so analytics information is prepared and available before it is needed for decision-making. This eliminates the waiting period where productivity is lost, as the analytics engine is already processing messages and generating insights proactively rather than reactively.
Data Source
AI summary
An overlay system is provided that includes a storage element and processing circuitry. The storage element stores an executable graph-based model that includes various executable nodes that communicate with each other by way of messages. The executable graph-based model further includes a message node for each message associated with the overlay system. Each message node is associated with one or more analytics overlay nodes that execute a corresponding set of analytics operations on composition of the corresponding message node to generate one or more analytic insights. The composition includes data and transactional information associated with the corresponding message node. A publisher overlay node associated with the one or more analytics overlay nodes may generate and publish an analytics outcome based on an output of the execution of the set of analytics operations. The analytics outcome is indicative of performance of the overlay system.