Adaptive Network Resource Packaging for Latency Reduction
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Solution Overview
Problem
Existing static resource packaging systems are inefficient in dynamically adapting to changing user demands on websites, leading to suboptimal resource grouping and increased latency, bandwidth waste, and unnecessary processing overhead.
Innovation Solution
An optimization algorithm that analyzes actual user requests over time to identify optimal groupings of resources for packaging, reducing the number of subsequent requests and improving network performance by predicting frequently requested resources and packaging them together.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static resource packaging systems are used with build-time grouping, then resource packaging is simple and deterministic, but the system cannot adapt to changing user demands and website evolution
Solution Approach 1:
The patent implements dynamic resource packaging by transitioning from static build-time grouping to runtime adaptive grouping. The system continuously monitors actual resource requests and usage patterns, then dynamically adjusts package compositions to match current user demands and website evolution, resolving the contradiction between adaptability and complexity through controlled dynamic behavior.
Solution Approach 2:
The system incorporates feedback mechanisms where actual resource request data and usage patterns are collected, analyzed, and used to refine future packaging decisions. This closed-loop feedback enables the system to learn from actual user behavior and continuously optimize package selections, achieving adaptability while managing complexity through data-driven iterations.
2Loss of energy
If all static resources are packaged together into one package, then packaging simplicity is maintained, but bandwidth is wasted and unnecessary data transmission occurs
Solution Approach 1:
The patent segments resources into multiple packages based on actual usage patterns and request correlations. Instead of treating all resources as a single unit, the system divides them into smaller, more targeted packages that can be selectively transmitted based on actual user needs, reducing bandwidth waste while managing complexity through intelligent segmentation.
Solution Approach 2:
The system applies local quality optimization by customizing package compositions for different users, contexts, and request patterns. Rather than using a uniform packaging approach for all resources, the system tailors package selections to local conditions and actual usage scenarios, minimizing unnecessary data transmission while maintaining manageable grouping complexity.
3Speed
If resources are packaged individually and transmitted separately, then packaging complexity is minimized, but latency increases due to multiple round trip requests
Solution Approach 1:
The patent merges multiple resource requests into consolidated packages that can be transmitted in single round-trip operations. By strategically combining frequently co-requested resources into unified packages, the system reduces the number of separate network round trips, thereby decreasing latency while managing packaging complexity through intelligent resource consolidation.
4Productivity
If build-time resource grouping is used, then packaging is deterministic and simple to implement, but the system becomes suboptimal quickly as websites evolve
Solution Approach 1:
The system performs preliminary analysis of resource usage patterns and predicts future packaging needs before finalizing package compositions. By proactively identifying emerging usage trends and preparing adaptive packages in advance, the system maintains high packaging efficiency while extending the validity duration of resource groupings through anticipatory optimization.
Data Source
AI summary
In one embodiment, a method includes accessing a data store comprising a log of requests transmitted by a plurality of remote hosts, each request corresponding to one or more resources maintained by a web site; analyzing the requests and one or more attributes of the resources corresponding to the respective requests using a cost function relating to network performance, wherein a first component of the cost function is directed to a performance improvement achieved by grouping one or more of the resources for transmission to one or more remote hosts and a second component is directed to a performance inefficiency caused by grouping the one or more resources for transmission to the one or more remote hosts; and identifying one or more groupings of one or more resources that optimize the cost function for network performance.