Network Page Latency Reduction via Probability Distribution Analysis
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Solution Overview
Problem
Network page latency varies significantly among users due to multiple queue-based processes involved in loading web pages, which existing technologies have not effectively addressed.
Innovation Solution
A closed-loop communication management system that collects latency data, calculates probabilities, estimates probability distributions, identifies latency-increasing attributes, and generates recommendations for modifications such as adjusting content delivery networks or call graphs to reduce latency, implemented through a network page latency reducer application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple queue-based processes are used to handle network page requests, then the system can handle more requests, but the network page latency increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing probability distributions for different queue configurations and page types. When a request arrives, the system retrieves pre-computed latency predictions rather than calculating them in real-time, significantly reducing the time penalty associated with multiple queue-based processes while maintaining the ability to handle high request volumes
Solution Approach 2:
The system implements feedback by continuously monitoring actual latency measurements and using them to refine and update the probability distributions. This closed-loop approach allows the system to learn from past performance and optimize queue configurations dynamically, balancing the trade-off between handling capacity and latency
2Loss of time
If existing technologies are used to address latency, then some latency reduction is achieved, but the significant variation in loading times among different users remains unaddressed
Solution Approach 1:
The patent applies local quality by creating user-specific or context-specific probability distributions based on individual user characteristics, network conditions, and historical behavior patterns. Instead of applying a uniform latency reduction approach to all users, the system tailors optimizations to each user's specific situation, thereby addressing both latency reduction and the variation in loading times across different user experiences
Data Source
AI summary
Network page latency reduction is facilitated by various embodiments. In one embodiment, a first distribution corresponding to a plurality of instances of a network page is estimated. A second distribution corresponding to a subset of the instances is also estimated. The network page is adapted based at least in part on a comparison of the first and second distributions in order to reduce network page latency.