Heuristic Path Computation for Label Switched Paths
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In large computer networks, constraint-based path computation for Multiple Label Switched Paths (LSPs) is complex, time-consuming, and resource-intensive, especially as available bandwidth is reduced with each LSP loaded, leading to network congestion and slow convergence in case of failures.
Innovation Solution
A path computation device computes a result set of multiple paths between network nodes using recursive or heuristic algorithms to identify locally-optimal paths for a cost function, allowing for pre-computation of diverse paths to spread traffic evenly and serve as alternate routes in case of failures, thereby reducing the need for real-time recalculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If constraint-based path computation is performed for each LSP in real-time, then accurate path selection is achieved, but computational time and resources increase significantly
Solution Approach 1:
The patent pre-computes multiple candidate paths between node pairs before they are needed for LSP establishment. By calculating and storing these paths in advance using recursive or heuristic algorithms, the system avoids performing complex constraint-based computations in real-time when LSPs need to be established, thus reducing computational time while maintaining path selection accuracy.
Solution Approach 2:
The system pre-identifies a set of candidate paths for each node pair and stores them in a database. When an LSP needs to be established, the system simply retrieves pre-computed paths and selects from them based on current network conditions, rather than performing full constraint-based path computation from scratch.
2Productivity
If multiple LSPs are loaded into the network, then network capacity is increased, but available bandwidth for each LSP is reduced leading to congestion
Solution Approach 1:
The patent segments the network paths into multiple candidate routes between source and destination nodes. By maintaining multiple pre-computed paths with different characteristics, the system can distribute traffic across these segmented paths, preventing any single path from becoming congested while still providing high network capacity.
Solution Approach 2:
The system dynamically selects from pre-computed candidate paths based on current network conditions such as available bandwidth and congestion levels. This dynamic selection allows the network to adapt to changing conditions and distribute traffic efficiently across multiple LSPs, maintaining high capacity while avoiding congestion on individual paths.
3Measurement precision
If complex constraint-based path computation is performed, then optimal paths are found, but device complexity and computational overhead increase
Solution Approach 1:
The patent performs complex path computation in advance during off-peak periods and stores the results. This preliminary action moves the computational burden away from real-time operations, reducing the complexity of devices that need to make quick path decisions while still achieving optimal path selection when LSPs are established.
Solution Approach 2:
The system creates copies of pre-computed path information and stores them in a database for quick retrieval. Instead of performing complex computations repeatedly, the system uses these pre-computed copies, significantly reducing computational overhead while maintaining path optimization quality.
Data Source
AI summary
In some examples, a path computation device is configured to compute, for a network of routers interconnected by a plurality of links in a network topology and based on a network topology model for the network topology, a first path that is a shortest path of the network topology model between a pair of nodes of the network topology model that represent a pair of the routers; increase, based on the first path, respective metrics for one or more links in the network topology model by respective finite values to obtain a modified network topology model; compute a second path that is a shortest path of the modified network topology model between the pair of nodes; and output data for at least one path of the first path and the second path to the network for programming a label switched path in the network on the at least one path.