VPN Server Selection via ISP Penalty Scoring
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Solution Overview
Problem
Most VPN services lack an inbuilt system to recommend or identify optimal VPN servers for user devices, leading to users randomly selecting servers without evaluating various parameters, resulting in unreliable connectivity and user experience.
Innovation Solution
A method that involves receiving a VPN servers request from a user device, obtaining the user's ISP and geolocation, calculating respective server penalty scores for available VPN servers, adjusting these scores using ISP data, and transmitting the optimal VPN server to the user device based on the adjusted scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If users randomly select VPN servers without evaluation, then device complexity is reduced, but reliability of connectivity deteriorates
Solution Approach 1:
The system performs preliminary evaluation of VPN servers by calculating penalty scores based on ISP data, geolocation, and connection histories before user selection. This advance assessment ensures reliable connectivity recommendations without requiring complex real-time decision-making by the user.
Solution Approach 2:
The VPN system automatically evaluates and ranks servers using automated penalty score calculations based on collected data about ISP blocking patterns, geolocation, and connection success rates. This self-service mechanism eliminates the need for manual server evaluation while ensuring reliable recommendations.
2Reliability
If VPN services implement server recommendation systems, then reliability of connectivity improves, but device complexity increases
Solution Approach 1:
The server selection system is segmented into independent components: data collection about ISPs and geolocations, penalty score calculation for each server, and recommendation generation. This modular approach improves connectivity reliability through comprehensive evaluation while managing complexity through clear separation of functions.
Solution Approach 2:
The system uses penalty scores as a parameter to represent server quality, transforming complex multi-factor evaluation (ISP blocking, geolocation, connection history) into a single comparable metric. This parameter transformation simplifies the decision-making process while maintaining reliable recommendations.
3Adaptability or versatility
If VPN services collect and analyze ISP data for each user, then adaptability to user conditions improves, but loss of information increases due to data processing requirements
Solution Approach 1:
The system extracts only the essential data elements needed for server selection: ISP identification, geolocation information, and connection success/failure outcomes. By taking out only these critical pieces of information rather than collecting all possible user data, the system achieves high adaptability while minimizing information processing overhead.
Solution Approach 2:
The system performs preliminary data collection and processing about ISPs and geolocations before actual VPN connection attempts. This advance preparation creates reusable knowledge about which servers work with which ISPs in which locations, reducing the need for extensive real-time data processing and improving adaptability efficiently.
Data Source
AI summary
An Internet Service Provider (ISP) of a user device is identified. At least one VPN server of available VPN servers is identified based on data indicative of respective histories of successful connections from devices in a location of the user device to the available VPN servers via the ISP, The at least one VPN server is then transmitted to the user device.