Cloud Wi-Fi QoE Metric via Queue Delay Analysis
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Solution Overview
Problem
Traditional Wi-Fi network management systems using local Wi-Fi network controllers are limited by vendor restrictions and require on-premise deployment, and existing performance metrics do not accurately reflect the quality of user experience for different applications, especially under varying traffic conditions.
Innovation Solution
A cloud-based Wi-Fi service manager with a cloud-based AP agent that can manage third-party APs remotely, using a device-specific abstraction layer to interface with various hardware and firmware, and an application logic layer to collect and analyze metrics such as queue delays and utilization, providing a quality-of-experience (QoE) metric that estimates application-level performance without adding extra traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional local Wi-Fi network controllers are used, then network management is achieved, but vendor restrictions and on-premise deployment requirements limit flexibility and adaptability
Solution Approach 1:
The patent introduces a cloud-based service manager as an intermediary between network administrators and Wi-Fi access points. This cloud-based intermediary eliminates the need for on-premise controllers, allowing remote management of multi-vendor APs through a centralized cloud platform, thereby resolving the contradiction between adaptability and infrastructure complexity
Solution Approach 2:
The patent transitions the network management architecture from a local/on-premise dimension to a cloud-based dimension. By moving the service manager to the cloud, the system achieves vendor-agnostic management and remote deployment capabilities without requiring physical presence at network locations, effectively resolving the deployment flexibility contradiction
2Measurement precision
If traditional network performance metrics are used, then network quality is visualized, but actual user experience quality for different applications is not accurately reflected
Solution Approach 1:
The patent implements a feedback mechanism where the cloud-based service manager continuously collects performance metrics from access points, analyzes application-level performance data, and uses this feedback to generate accurate QoE metrics. This closed-loop feedback system enables precise measurement of actual user experience quality by correlating network metrics with application performance outcomes
Solution Approach 2:
The patent introduces an application logic layer as an intermediary between raw network metrics and user experience assessment. This intermediary layer processes and correlates metrics from multiple sources (throughput, delay, packet loss) with application-specific requirements, transforming basic network statistics into accurate QoE measurements that truly reflect user experience
3Adaptability or versatility
If cloud-based service manager with device-specific abstraction layer is implemented, then multi-vendor AP management is enabled, but system architecture complexity increases
Solution Approach 1:
The patent segments the cloud-based service manager into distinct functional layers: a device-specific abstraction layer that handles vendor-specific protocols and a unified management layer that provides vendor-agnostic control. This segmentation allows the system to manage multiple vendor APs through standardized interfaces while maintaining compatibility with diverse hardware, resolving the contradiction between adaptability and architectural complexity
Data Source
AI summary
A method of evaluating an application performance metric of a Wi-Fi device that is running an application and that is receiving application data from another Wi-Fi device transmitting the application data is disclosed. An indication of a delay in one or more of a plurality of access category queues at the Wi-Fi device transmitting the application data is received. The delay over time is characterized, wherein the characterization of the delay over time includes a statistical measure of the delay determined based on the received indication of the delay in the one or more of the plurality of access category queues. An application quality-of-experience (QoE) metric is determined based on a mapping from the characterization of the delay over time to an application performance.