Application QoE Analytics for Remote vs Office Network Experience
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Solution Overview
Problem
There is limited visibility into the application quality of experience (QoE) for remote workers, making it difficult to determine whether they experience better QoE in the office or at a remote location, as factors beyond the enterprise's control can significantly impact their network connection and application performance.
Innovation Solution
A device maps network addresses to geographical locations, obtains QoE metrics, and determines whether the office location would provide a better experience, using machine learning to predict and optimize application performance by rerouting traffic to ensure SLA compliance and enhance user satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If remote work options are implemented to improve work flexibility, then employee productivity and satisfaction are improved, but visibility into application QoE and control over network performance deteriorate
Solution Approach 1:
The patent introduces an intermediary system comprising a QoE collector, analyzer, and mapper that mediates between remote users and enterprise network administrators. This intermediary collects QoE metrics from remote users, analyzes the data, maps network addresses to geographical locations, and provides insights to administrators without requiring direct control over remote networks, thus resolving the contradiction between work flexibility and QoE visibility
Solution Approach 2:
The system implements a feedback mechanism where QoE metrics are continuously collected from remote users, analyzed, and fed back to network administrators. This feedback loop enables administrators to monitor and understand application performance for remote workers, maintaining visibility and control while allowing remote work flexibility
2Adaptability or versatility
If remote workers use various network connections (home networks, mobile networks) to improve work flexibility, then adaptability is improved, but network performance and application QoE deteriorate due to factors beyond enterprise control
Solution Approach 1:
The system monitors and analyzes multiple QoE parameters (latency, packet loss, jitter, throughput) for different network connections used by remote workers. By tracking these parameters across various network types (home networks, mobile networks, office networks), the system can identify performance patterns and provide insights to improve application QoE reliability regardless of the network connection being used
Solution Approach 2:
The system performs preliminary analysis of QoE metrics and network conditions before issues affect productivity. By proactively monitoring network performance and predicting potential QoE problems, the system enables preventive actions to be taken, such as recommending network optimizations or alternative connections, thereby maintaining application reliability across diverse network environments
Data Source
AI summary
In one embodiment, a device maps network addresses associated with a user to a plurality of geographical locations, at least one of which is an office location of an enterprise. The device obtains quality of experience metrics for an online application accessed by the user. The device makes, based on the quality of experience metrics, a determination as to whether the office location of the enterprise would afford better application experience to the user. The device provides an indication of the determination for display.