Application-Aware Link Recovery for Pattern-Driven Error Isolation
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Solution Overview
Problem
Existing network link failure management systems shut down links based on aggregate error thresholds, disregarding application-specific error contributions, leading to unnecessary connectivity disruptions and suboptimal network performance.
Innovation Solution
Implement application-aware link monitoring and recovery systems that identify and isolate application-specific traffic streams causing errors, allowing for targeted corrective actions such as rerouting or modifying data patterns to mitigate errors without shutting down the entire link.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aggregate error threshold monitoring is used to manage link failures, then link reliability is improved by shutting down faulty links, but network connectivity is worsened by unnecessary shutdowns of links with acceptable performance
Solution Approach 1:
The patent segments aggregate network traffic into distinct application-specific streams, allowing independent error monitoring for each application. This segmentation enables the system to identify that errors are confined to specific applications rather than affecting the entire link, preventing unnecessary link-wide shutdowns while maintaining reliability for affected applications.
Solution Approach 2:
The patent implements local quality control by applying error thresholds and monitoring mechanisms specifically to individual application traffic streams rather than uniformly to all traffic on the link. This allows the system to maintain different error tolerance levels for different applications, shutting down only the specific application stream causing errors while preserving connectivity for other applications on the same link.
2Reliability
If link shutdown is used as corrective action for error conditions, then error propagation is prevented, but link utilization is reduced by taking the entire link offline
Solution Approach 1:
The patent extracts and isolates the problematic application-specific traffic stream from the aggregate link traffic. By identifying and separating the specific application causing errors through application tagging and stream-specific monitoring, the system can apply corrective actions only to that particular stream rather than shutting down the entire link, thus preventing error propagation while maintaining link utilization for other applications.
3Productivity
If application-specific error monitoring is implemented, then network performance is optimized by targeted corrective actions, but system complexity increases due to additional monitoring and tagging mechanisms
Solution Approach 1:
The patent implements a universal application tagging mechanism that can be applied across multiple applications and traffic streams. The tagging system serves multiple functions: identifying application sources, enabling stream-specific error monitoring, and facilitating targeted corrective actions. This multi-functional approach consolidates what could be multiple separate systems into a single unified framework, reducing overall complexity while enabling sophisticated application-aware link management.
Data Source
AI summary
The present technology is directed to a system and method for application aware management and recovery of link failures resulting from excessive errors observed on the link. One aspect of the proposed technology is based on identification of link errors associated with application-specific data patterns traversing link. Other aspects involve corrective actions based on relocation or modification of specific application traffic to thereby alleviate the observed excessive link errors and prevent a link failure or shut down. Relocation may involve moving the source application to a different virtual machine/container/physical device or rerouting application traffic by updating relevant routing protocols. Modification may involve harmlessly changing payload data pattern to remove data-pattern dependent signal attenuation. Information corresponding to identified faulty payload data patterns and associated frame data quality parameters maybe stored and utilized to provide analytics evaluation of network wide physical resource issues that maybe affecting application traffic.