Network Issue Validation via Automated Simulation
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Solution Overview
Problem
Current network deployment methods require extensive configuration and administration by skilled engineers, making it difficult and time-consuming to integrate wired and wireless devices, manage device mobility, and secure networks, especially with the rise of IoT devices and BYOD capabilities, leading to inefficiencies in adopting new technologies like video collaboration and connected workspaces.
Innovation Solution
A system that uses data collection and machine learning to simulate and validate network issues, allowing for independent issue detection and classification, and automated reproduction of issues to verify the accuracy of network management and assurance platforms, thereby simplifying network management and enhancing security and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration and administration by skilled network engineers is used to integrate wired and wireless devices, then network security and reliability can be maintained, but deployment time and complexity increase significantly
Solution Approach 1:
The network devices perform self-configuration and self-validation through automated issue simulation and detection. The system enables devices to automatically validate their own configurations by simulating potential issues and detecting problems without requiring manual intervention from network engineers, thereby reducing deployment time while maintaining security through automated validation processes
Solution Approach 2:
The system performs preliminary issue simulation and validation before actual network deployment or operation. By pre-simulating potential issues and validating configurations in advance, the system identifies and resolves problems before they affect network security or performance, enabling faster deployment with confidence in system reliability
2Reliability
If extensive manual configuration and administration is performed to manage device mobility and integrate diverse devices, then network reliability is improved, but operational complexity and time consumption increase
Solution Approach 1:
The automated issue validation system enables network devices to self-manage configuration validation and mobility management. Devices automatically simulate and detect issues related to their configuration and mobility events without requiring skilled engineers to manually manage each device, reducing operational complexity while maintaining network reliability through continuous automated validation
Solution Approach 2:
The system implements continuous feedback loops where network devices automatically report configuration status and mobility events, which are then validated through issue simulation. This automated feedback mechanism allows the system to maintain network reliability by continuously monitoring and validating device states without requiring manual intervention, thereby reducing operational complexity
3Productivity
If automated issue simulation and validation is implemented, then deployment time and operational complexity are reduced, but system complexity and validation requirements increase
Solution Approach 1:
The automated validation system is segmented into modular components: issue simulation modules, event sequence identification modules, and validation modules. Each component performs a specific function independently, allowing the system to achieve high deployment speed through automated processes while managing complexity through modular architecture that can be independently configured and maintained
Data Source
AI summary
Systems, methods and computer-readable storage media are provided for detecting and simulating issues in a network. The methodology includes identifying: event sequences within network traffic data; filtering out a subset of the event sequences based on characteristics of the subset of the event sequences; generating definition groups by performing clustering on the subset of the event sequences, the definition groups comprising event sequence characteristics associated with one or more network issues; first simulating the subset of the event sequences; generating, based on results of the first simulating, a first issue identification; second simulating a most recent one of the identified event sequences; generating, based on results of the second simulating and the generated definition groups, a second issue identification; and validating the first issue identification with the second issue identification.