Throttled Scanning for Client-Side Data Compression
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Solution Overview
Problem
Current methods for communicating compressed data over the Internet, particularly for streaming content and user interaction data, face challenges in ensuring seamless performance, especially with limited bandwidth, and lack efficient optimization techniques for data compression and caching.
Innovation Solution
The implementation of client-side compression systems that utilize throttled scanning processes, batch processing, and caching to optimize the compression of instrumentation data, accelerate caching options, and ensure seamless content streaming by compressing tracked content, page view, and user interaction data before transmission to a server.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression is performed continuously without throttling, then compression efficiency is improved, but processing overhead and impact on main application performance worsen
Solution Approach 1:
The patent implements throttled scanning that periodically scans instrumentation data at controlled intervals rather than continuously processing all data. This periodic action reduces CPU overhead and allows the main application to run smoothly while still achieving effective compression of tracked content, page view, and user interaction data.
Solution Approach 2:
The system performs preliminary scanning and identification of data patterns before actual compression occurs. By pre-processing and throttling the scanning rate, the system prepares data for compression in advance, reducing the computational burden during the actual compression phase and minimizing impact on real-time application performance.
2Loss of time
If all instrumentation data is scanned and compressed in real-time, then data freshness is improved, but bandwidth consumption and processing time worsen
Solution Approach 1:
The patent extracts and separates critical instrumentation data (tracked content, page views, user interactions) from the full data stream for selective compression. By taking out only the most important data elements rather than processing everything in real-time, the system maintains data freshness for key metrics while reducing overall bandwidth consumption.
Solution Approach 2:
The system applies different processing qualities to different data types based on their importance. Critical user interaction data receives higher priority processing with faster compression, while less critical instrumentation data is processed at lower priority. This local quality differentiation optimizes both data freshness and bandwidth usage.
3Loss of substance
If compression processing is intensified to handle large data volumes, then compression ratio is improved, but impact on main application performance worsens
Solution Approach 1:
The patent implements partial processing where only a throttled subset of instrumentation data is scanned and compressed at any given moment. This partial action approach achieves sufficient compression ratios for the most important data while leaving enough computational resources for the main application to maintain its performance and reliability.
Data Source
AI summary
A system can throttle compression of instrumentation data related to a page view, by throttled scanning processes. Then that data can be communication over the Internet to a server effectively. The scanning of instrumentation data can be performed via batch processing; and therefore, data for compression may be maximized or throttled. The system can also accelerate the various caching options involved with the streaming of content items and ad items. For example, such items can be retrieved by the local and/or remote caches associated with the client-side application and/or the page view, prior to the items being requested by and/or presented to a user, via batch retrieval processes. These batch retrieval processes can also be combined with the batch scanning processes.