Client-Side Data Compression for Streaming Analytics
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Solution Overview
Problem
Current methods for communicating compressed data over the Internet for analysis are inefficient, particularly in delivering seamless content with limited bandwidth, and existing data compression techniques do not adequately address the growing amount of content and user interaction data being tracked.
Innovation Solution
Implementing a client-side compression system that scans, builds, serializes, and compresses data on a client device, allowing for efficient communication of large amounts of data by utilizing a client-side application like a web browser to compress instrumentation data, including content, page view, and user interaction data without refreshing the user interface, and using a cache to stream content seamlessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compressed using conventional methods, then data size is reduced, but compression speed and efficiency are insufficient for real-time streaming content
Solution Approach 1:
The patent segments the compression process into distinct modules: scanning section identifies content sections, building section creates data models, serialization section converts to transmittable format, and compression section reduces data size. This segmentation allows each module to operate independently and efficiently, improving overall compression speed while maintaining effectiveness.
Solution Approach 2:
The patent performs preliminary actions by scanning and identifying content sections before compression, building data models in advance, and serializing data structures prior to the actual compression operation. This preliminary processing optimizes the compression phase and enables real-time performance.
2Loss of information
If more content and user interaction data are tracked, then analytics capability is improved, but bandwidth consumption increases
Solution Approach 1:
The patent applies local quality by compressing only the specific sections of content that are actually viewed or interacted with, rather than compressing entire pages or documents. This selective approach maintains analytics data completeness for viewed portions while significantly reducing bandwidth consumption for unviewed content.
Solution Approach 2:
The patent extracts and compresses only the necessary tracked data portions related to user interactions and viewed content sections, separating this from unnecessary data. This extraction approach ensures analytics capability is maintained for relevant data while minimizing bandwidth usage by excluding redundant information.
3Speed
If data is compressed and transmitted in real-time, then streaming seamlessness is improved, but compression complexity increases
Solution Approach 1:
The compression system is divided into four distinct sections (scanning, building, serialization, compression) that can be independently optimized and maintained. This segmentation reduces the complexity burden on any single component while enabling real-time processing through parallel operation of the sections.
Solution Approach 2:
The patent creates a universal compression framework that handles multiple data types (content sections, user interactions, tracking data) through a single integrated system. This multi-functional approach reduces overall system complexity compared to having separate compression systems for each data type, while maintaining real-time transmission capability.
Data Source
AI summary
A system can stream content items and ad items to a user interface of a client-side application (such as a web browser) without refreshing the user interface and by requesting such items from a local cache and/or a remote cache associated with the client-side application or the user interface. The remote cache can operate much like a local cache for the client-side application or the user interface. Items can be streamed to a user interface without refreshing the user interface and by requesting such items from a remote cache dedicated to caching the items that can be presented by the user interface. Because the tracking of such items and the tracking of the interactions with such items creates such large amounts of data, communicating the tracked data may be impracticable without use of a system that can effectively compress associated instrumentation data.