Client Event Timeline Branching for Low-Bandwidth Data Logging
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Solution Overview
Problem
Existing application instrumentation and event tracking methods consume significant computing resources and bandwidth on client devices, leading to long instrumentation cycles and inefficient data processing.
Innovation Solution
Implement a specialized data logging feature on client devices that processes events using a plug-in architecture, enabling efficient data collection, filtering, and enrichment before forwarding to designated destinations, with optional clean-up steps to optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional application instrumentation methods are used to collect and send event data to destination servers, then complete data collection is achieved, but computing resource consumption and bandwidth usage increase significantly
Solution Approach 1:
The patent segments the event data processing pipeline into multiple stages: event generation, enrichment, filtering, and forwarding. By dividing the processing into discrete stages with intermediate storage in an event timeline, the system reduces the computational burden at any single point and allows for selective processing of events based on filtering criteria, thereby reducing overall computing resource consumption while maintaining data collection completeness.
Solution Approach 2:
The patent implements preliminary filtering and enrichment actions before events are forwarded to destination servers. Events are pre-processed, enriched with additional context, and filtered based on criteria before leaving the client device. This preliminary action reduces the volume of data that needs to be transmitted and processed remotely, decreasing bandwidth usage and remote computing resources while ensuring complete and accurate data collection.
2Measurement precision
If comprehensive event data is collected and transmitted to destination servers, then analytics accuracy is improved, but bandwidth requirements increase
Solution Approach 1:
The patent applies local quality by enriching events with context-specific information at the source (client device) before transmission. Different event types receive different levels and types of enrichment based on their specific requirements. This localized enrichment ensures that only necessary and relevant data is transmitted, improving analytics accuracy while minimizing bandwidth consumption by avoiding transmission of redundant or unnecessary information.
Solution Approach 2:
The system performs preliminary enrichment and filtering of event data before transmission to destination servers. Events are enhanced with relevant context information and filtered to include only those meeting specific criteria, ensuring high analytics accuracy. This preliminary processing reduces the total volume of data transmitted over the network, thereby reducing bandwidth consumption while maintaining comprehensive analytics capability.
3Speed
If event processing is performed on client devices with minimal filtering, then processing speed is maintained, but device resource consumption increases
Solution Approach 1:
The patent segments event processing into distinct stages: quick filtering based on simple criteria, selective enrichment for events passing the filter, and structured storage in an event timeline. This segmentation allows the system to perform rapid initial filtering that consumes minimal resources, while more resource-intensive enrichment operations are performed only on a subset of events, thereby maintaining processing speed while reducing overall device resource consumption.
Solution Approach 2:
The system applies partial processing by performing comprehensive enrichment and analysis only on events that pass initial filtering criteria. Rather than processing every event with full resource allocation, the system performs minimal initial processing on all events and more intensive processing only where necessary. This partial action approach maintains processing speed for the overall event stream while significantly reducing device resource consumption.
Data Source
AI summary
Described are systems, methods, and computer-readable storage mediums for processing an event that is detected on a client device. The event is processed at a first data stream corresponding to a first branch of an event processing timeline. The processing of the event at the first data stream includes performing initial processing and initial data enrichment of data associated with the event. After the initial processing and data enrichment, the event is processed at a second data stream corresponding to a second branch of the event processing timeline in parallel with the processing of the event at the first data stream. The processing of the event at the second data stream includes performing additional initial data processing and additional data enrichment of the data associated with the event. The additional initial data processing and the additional data enrichment is specific to a destination associated with the event. After the additional initial data processing and the additional data enrichment, the event is conditionally forwarded to the destination associated with the second branch.