LFA Path Algorithms Caching Shortest Paths
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Solution Overview
Problem
Existing network routing technologies face inefficiencies in calculating backup paths, particularly in large networks, leading to prolonged convergence times and limited scalability due to increased computational efforts proportional to the number of neighbor routers or total network elements.
Innovation Solution
A modified process based on the Dijkstra shortest path algorithm, comprising three passes: the first pass calculates unconditional shortest paths, the second pass computes loop-free alternative backup paths leveraging cached data, and the third pass determines remote backup paths, prioritizing candidate paths by distance to enhance computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard LFA backup path calculation is performed using routing protocols, then backup paths can be computed for network failures, but the computational effort increases proportionally to the number of neighbor routers or total network elements, leading to prolonged convergence times
Solution Approach 1:
The patent pre-calculates and caches shortest path information and reverse shortest path information before failures occur. When a link or node failure happens, the backup path is quickly determined by checking pre-computed data structures rather than performing full shortest path calculations, dramatically reducing convergence time while maintaining backup path availability
Solution Approach 2:
The patent divides the backup path calculation into separate phases: pre-computation of shortest paths and reverse shortest paths, followed by quick lookup during failure events. This segmentation allows the system to prepare computational data in advance, separating the heavy computational workload from the time-critical failure response
2Reliability
If comprehensive backup path calculation is performed across the entire network topology, then all possible failure scenarios are covered, but the computational complexity increases significantly in large networks
Solution Approach 1:
The patent creates simplified data structures (shortest path cache and reverse shortest path cache) that copy essential topology information in a compressed format. These cached representations allow complex backup path calculations to be performed using simple table lookups and comparisons, reducing computational complexity while maintaining comprehensive failure coverage
Solution Approach 2:
The patent changes the computational parameters from calculating full backup paths on-demand to pre-computing and storing only the essential shortest path distances and next-hop information. This parameter transformation reduces the complexity from O(n^2) or worse to O(n) for path determination, where n is the number of network nodes
Data Source
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AI summary
A method is implemented by a network element to improve efficiency of loop free alternative (LFA) path computation by caching data from a shortest path first calculation for use in the LFA path calculation. The shortest path first calculation determines a shortest path from a source vertex to each vertex in a network topology graph representing the network in which the network element operates, where an endpoint for each shortest path is the shortest path vertex, and where each shortest path determined by the shortest path first calculation is stored.