VPN Server Selection Using Creation Time Penalty Scores
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Most VPN services lack an inbuilt system to recommend or identify optimal servers for users, leading to ambiguity in server selection and potential issues with connectivity and performance.
Innovation Solution
The development of systems and methods to dynamically evaluate and identify optimal VPN servers by computing server penalty scores based on various conditions such as location, load, and proximity to international Internet exchange hubs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If VPN services do not have an inbuilt system to recommend or identify optimal servers, then device complexity is reduced, but reliability and user experience deteriorate due to ambiguity in server selection and potential connectivity issues
Solution Approach 1:
The VPN server selection system operates autonomously by automatically evaluating multiple servers based on predefined criteria (location, load, proximity to exchange hubs) and selecting the optimal one without requiring user intervention. The system self-manages the complexity of server evaluation while presenting a simple connection interface to users, thus improving reliability without significantly increasing user-facing complexity
Solution Approach 2:
The system performs preliminary evaluation and scoring of multiple VPN servers before connection is established. By pre-calculating penalty scores based on server conditions and assigning weights to different criteria, the system prepares the optimal server selection in advance, ensuring reliable connectivity is achieved automatically without requiring complex real-time decision-making during user connection
2Productivity
If multiple VPN servers are available without an evaluation system, then adaptability is improved, but productivity decreases due to ambiguous server selection and potential connectivity issues
Solution Approach 1:
The system transforms qualitative server conditions (location, load, proximity to exchange hubs) into quantitative penalty scores by assigning numerical weights to each parameter. This parameter transformation enables objective comparison and automatic selection of the optimal server, improving connection productivity through systematic evaluation rather than random or manual selection
Solution Approach 2:
The system continuously monitors server conditions and uses this feedback to dynamically update penalty scores and server rankings. By incorporating real-time information about server load, location, and connectivity status into the evaluation process, the system ensures that the selected server optimizes connection speed and productivity based on current network conditions
Data Source
AI summary
A request is received from a user device. In response to the request, respective penalty scores for VPN servers are calculated. A respective penalty score for a VPN server is calculated based on a time of creation of the VPN server such that a first VPN server of the VPN servers having a first creation time that is earlier in time than a second creation time of a second VPN server of the VPN servers is assigned a higher weight than the second VPN server. One or more of the VPN servers are selected based on the respective penalty scores. Respective internet protocol (IP) addresses of the one or more of the VPN servers are transmitted to the user device.