Digital Model Persona for Proactive Network Resource Testing
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Solution Overview
Problem
Existing network monitoring systems lack the ability to automatically test network resources before users perform tasks, leading to potential outages and productivity losses when resources become unavailable.
Innovation Solution
The implementation of digital model personas that mimic the network activities of human users, allowing for pre-testing of network resources before actual task execution, and providing notifications and schedule adjustments when resources are unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network monitoring systems wait for devices to report performance issues, then system complexity is reduced, but network reliability deteriorates due to reactive rather than proactive monitoring
Solution Approach 1:
The patent implements preliminary action by having the digital model persona proactively test network resources before the actual user task execution time. The system schedules pre-tests at a predetermined time prior to when the user needs to access network resources, allowing potential issues to be detected and addressed before they impact productivity.
Solution Approach 2:
The patent uses copying by creating a digital model persona that replicates the network activity patterns of actual users. This digital twin copies user behavior, task schedules, and network resource usage patterns, allowing the system to simulate and test network availability without interfering with actual user operations.
2Loss of time
If network monitoring only occurs after tasks are scheduled, then measurement precision is improved, but loss of time increases due to reactive response
Solution Approach 1:
The system performs network resource testing in advance before the user needs to access these resources. By scheduling pre-tests at a predetermined time prior to task execution, the system eliminates reactive response time and allows users to reschedule or adjust tasks before network issues occur.
Solution Approach 2:
The system implements feedback by continuously monitoring network resource availability and comparing it against scheduled task requirements. When the digital model persona detects that a network resource will be unavailable at the scheduled task time, the system provides feedback to allow users to reschedule or adjust their tasks proactively.
3Productivity
If digital model personas perform pre-testing of network resources, then productivity is improved by preventing task failures, but device complexity increases
Solution Approach 1:
The patent creates a digital model persona that copies user network behavior patterns, task schedules, and resource usage preferences. This digital twin allows the system to simulate and test network availability without requiring complex integration with actual user workflows, maintaining simplicity while improving productivity.
Solution Approach 2:
The system implements self-service by having the digital model persona automatically perform pre-testing of network resources based on scheduled tasks. The system autonomously detects availability issues and notifies users without requiring manual intervention, thereby improving productivity while keeping the interface simple.
Data Source
AI summary
A network management system tests the availability of a network resource before a user performs a task with the network resource. The system measures network activity of a user performing one or more tasks. The network activity includes communication between a user device of the user and each network resource associated with a corresponding task performed by the user. The system also generates a digital model persona of the user based on the tasks performed by the user, and determines a schedule of the tasks performed the user. Each particular task is associated with a corresponding execution time for the user. The system further configures the digital model persona to test the network resource associated with each corresponding task at a testing time that is a predetermined length of time prior to the execution time for the user.