Predicted Web Object Caching for Low-Bandwidth Browsing
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Solution Overview
Problem
Web browsing on networks with low bandwidth and high latency is inefficient, leading to prolonged download times and poor user experience, particularly in wireless WANs where bandwidth and latency constraints are exacerbated by interference and noise, and the existing HTTP protocol over TCP/IP does not effectively manage the complexity of modern web pages with multiple objects from different servers.
Innovation Solution
A system comprising a user agent, client device, optimization server, and content servers that employs data caching, predicted request generation, and response optimization to reduce latency and bandwidth usage by caching frequently accessed objects, predicting request data, and optimizing response processing, thereby minimizing the need for repeated requests to content servers and improving download efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If web browsing is performed on networks with low bandwidth and high latency, then network coverage and accessibility are improved, but download time and user experience deteriorate
Solution Approach 1:
The system performs preliminary actions by predicting which objects will be requested before they are actually requested. The prediction engine analyzes historical data and current context to pre-fetch and cache objects in advance, so when the user actually requests them, they are already available locally, eliminating the need for slow network transfers.
Solution Approach 2:
Instead of transferring original objects over the slow network, the system creates and stores copies of predicted objects in the local cache. When objects are needed, the cached copies are used directly, bypassing the bandwidth-constrained network connection entirely.
2Adaptability or versatility
If traditional HTTP protocol is used to transfer content, then protocol compatibility and simplicity are maintained, but network efficiency and bandwidth utilization deteriorate
Solution Approach 1:
The system introduces an intermediary optimization server between the user agent and content servers. This intermediary intercepts HTTP requests, predicts additional objects that will be needed, and manages caching strategically. It maintains full HTTP protocol compatibility while adding intelligent optimization layers that improve bandwidth utilization and reduce unnecessary network transfers.
3Adaptability or versatility
If multiple objects from different servers are downloaded, then web page functionality and content variety are improved, but latency and complexity increase
Solution Approach 1:
The system merges multiple object requests into a single prediction and caching operation. Instead of separately downloading objects from multiple different servers, the prediction engine analyzes the collective needs and prefetches objects from multiple sources in coordinated batches, reducing the total number of separate network round-trips and minimizing latency.
4Adaptability or versatility
If network resources are shared among many users, then network accessibility and user base are improved, but bandwidth availability and transmission reliability deteriorate
Solution Approach 1:
The system creates local copies of objects in user-specific caches, making the content available independently of network conditions. Once an object is cached locally, it can be accessed reliably without being affected by network sharing, interference, or bandwidth contention that plagues wireless WAN environments.
Data Source
AI summary
A method including communicating with a content server, wherein the communication includes transmitting request data to the content server and receiving first response data associated with the request data; identifying response object data within the first response data; determining whether the response object data is to be downloaded; querying the content server for second response data that corresponds to the response object data based on the determination; transmitting the first response data to a user agent; and storing the second response data, wherein the second response data can be provided to the user agent in a subsequent request.