Square-Grid Location Abstraction for Cloud Experience Analysis
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Solution Overview
Problem
Existing computing systems face challenges in understanding and improving cloud experience without accurate user location data due to privacy regulations and user reluctance to disclose location information, making it difficult to optimize connectivity and user experience across enterprise networks.
Innovation Solution
A client-side system divides geographic areas into grid sections and provides a pre-defined reference location corresponding to the user's grid section, allowing for abstracted location data to be sent to a remote server, enabling analysis of cloud interaction metrics without precise user location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise user location data is collected, then cloud interaction metrics can be accurately analyzed, but user privacy is compromised and users are reluctant to provide data
Solution Approach 1:
The geographic area is divided into grid sections, and user location is mapped to a pre-defined reference location within the grid rather than precise coordinates. This segmentation approach maintains sufficient spatial resolution for metric analysis while eliminating personally identifiable location information, thus resolving the contradiction between measurement precision and privacy protection
Solution Approach 2:
A pre-defined reference location system acts as an intermediary between precise user location and analytical needs. The reference location serves as a proxy that preserves spatial context for cloud interaction metric analysis without exposing actual user position, thereby addressing both privacy concerns and analytical requirements
2Reliability
If multiple Internet egress points are provided for enterprise security, then network security is improved, but cloud experience optimization becomes more difficult due to limited location data
Solution Approach 1:
By dividing the service area into grid sections and assigning pre-defined reference locations, the system can effectively group and analyze user metrics across multiple egress points. This enables the cloud service to understand geographic patterns and provide location-specific optimization recommendations while enterprises maintain their multi-egress security architecture
Solution Approach 2:
The pre-defined reference location system serves as an intermediary that bridges the gap between multiple enterprise egress points and cloud service analysis. It provides sufficient geographic context for optimizing cloud experience across distributed egress points without requiring users to disclose precise location information
Data Source
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AI summary
A client-side system detects a current location of a client device and a cloud interaction metric. The geographic area around the location of the client device is divided into grid sections. The client-side system identifies a pre-defined reference location corresponding to the grid section that the client device location resides in. The pre-defined reference location, corresponding to that grid section, and the cloud interaction metric are provided to a remote server computing system.