Optical Transmission Device Recovery Resource Planning for N-Time Faults
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for planning recovery resources in transport networks to resist multi-time faults are costly and have poor reliability, as they require large quantities of resources and are based on empirical load settings, which do not effectively adapt to different fault scenarios.
Innovation Solution
A method for planning recovery resources on an optical transmission device that iteratively determines optimal recovery resources for (N-1)-time and N-time faults, using network planning information to select recovery resources based on specific fault scenarios, ensuring reliable service recovery with minimal resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preset recovery resources are planned for different services, then service recovery capability is provided, but a large quantity of recovery resources are required and the solution is costly
Solution Approach 1:
The patent implements a universal recovery resource planning method where recovery resources are planned once for the entire network to resist N-time faults, rather than planning separate recovery resources for each service. This single planning process determines optimal recovery resources that can serve multiple services simultaneously, reducing the total quantity of recovery resources required while maintaining reliable service recovery capability across all services.
2Reliability
If network light load technology is used to plan recovery resources, then service recovery success rate is improved, but costs increase and reliability of resisting multi-time faults is poor
Solution Approach 1:
The patent applies preliminary action by planning recovery resources in advance for the entire network to resist N-time faults before any faults occur. The system pre-determines optimal recovery resources based on network topology and fault scenarios, rather than reacting to faults individually or using empirical load settings. This preliminary planning ensures reliable service recovery capability while optimizing resource usage across all possible fault scenarios.
3Adaptability or versatility
If recovery paths are calculated in advance for each service, then service recovery is prepared, but different recovery paths cannot be selected according to different faults and a large quantity of recovery resources are required
Solution Approach 1:
The patent creates a universal recovery resource planning framework that determines optimal recovery resources once for the entire network to resist N-time faults. This single planning process produces recovery resources that can be adaptively selected for different fault scenarios and services, eliminating the need to calculate separate recovery paths for each service in advance. The system maintains high adaptability by selecting appropriate recovery resources based on current network state and fault conditions while using fewer total resources.
Data Source
AI summary
The present application provides a method for planning a recovery resource for resisting N-time faults and an optical transmission device, and the method includes: planning, on an optical transmission device according to preset network planning information, a recovery resource for resisting (N−1)-time faults for preset (N−1)-time faults, and the recovery resource for resisting (N−1)-time faults is an optimal recovery resource corresponding to each interrupted service during the preset (N−1)-time faults; and planning, by the optical transmission device according to the network planning information and the recovery resource for resisting (N−1)-time faults, a recovery resource for resisting N-time faults for preset N-time faults, where the recovery resource for resisting N-time faults is a network-wide optimal recovery resource corresponding to interrupted services during the N-time faults. According to the present application, recovery resource costs can be reduced, and recovery resource planning reliability can be improved.