Traffic Engineering in SPF Networks
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Solution Overview
Problem
Current traffic engineering methods in SPF-routed networks face challenges in accurately estimating point-to-point bandwidth demand and optimizing link metrics to prevent congestion, especially under network failures or topology changes.
Innovation Solution
A system and method that estimate point-to-point bandwidth demand by determining link traffic measures and calculating point-to-point bandwidth demand estimates, which are used to simulate network routing changes and optimize link utilizations, including identifying valid sets of link traffic values and bandwidth demand levels to minimize inconsistencies and maximize link utilization efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traffic engineering methods are used to optimize link metrics, then link utilization efficiency is improved, but measurement precision of point-to-point bandwidth demand deteriorates
Solution Approach 1:
The system performs preliminary actions by measuring link traffic measures and demand measures before optimizing link metrics. These preliminary measurements provide the data needed to calculate accurate point-to-point bandwidth demand estimates, which are then used to guide metric optimization while maintaining measurement precision.
Solution Approach 2:
The system implements feedback mechanisms where link traffic measures and demand measures are continuously monitored and used to refine bandwidth demand estimates. This feedback loop allows the system to adjust metric optimizations based on actual network conditions, maintaining both productivity and measurement precision.
2Reliability
If link metrics are optimized to prevent congestion, then network reliability is improved, but device complexity increases
Solution Approach 1:
The system segments the traffic engineering function into distinct modules: link traffic measure collection, demand measure collection, bandwidth demand estimation, and link metric optimization. This segmentation reduces overall system complexity by making each component independent and easier to manage while maintaining reliability through coordinated operation.
Solution Approach 2:
The system introduces intermediary components that mediate between network monitoring and optimization functions. These intermediaries process raw measurements into meaningful estimates and guide metric optimizations, reducing the complexity direct control would require while maintaining reliable congestion prevention.
3Productivity
If bandwidth demand estimation is performed accurately, then traffic engineering effectiveness is improved, but loss of time increases
Solution Approach 1:
The system applies partial action by measuring and calculating bandwidth demand estimates only for necessary link traffic measures and demand measures, rather than performing complete network analysis. This selective approach maintains traffic engineering effectiveness while reducing the time required for measurements and calculations.
Solution Approach 2:
The system implements continuous measurement and estimation processes that operate alongside network operations rather than requiring separate time periods. This continuity allows traffic engineering effectiveness to be maintained without significant time loss, as measurements and calculations proceed concurrently with network traffic.
Data Source
AI summary
A system, to migrate a shortest-path-first (SPF) routed network from a first routing state to a second routing state, includes a changeover module to generate a sequence of intermediate network plans, each of which modifies a preceding network state according to a preceding network plan, such that a routing of at least one demand in the network changes. The sequence of intermediate network plans migrates the network from the first routing state to the second routing state. A network controller sequentially configures the network according to the sequence of intermediate network plans to migrate the network from the first routing state to the second routing state. Each intermediate network plan of the sequence configures the network to operate within at least one predetermined constraint.


