P2MP LSP Path Optimization Using Link Penalties
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Solution Overview
Problem
Existing network technologies face challenges in efficiently computing and optimizing point-to-multipoint (P2MP) label switched paths (LSPs) in computer networks, particularly in managing resource costs, avoiding routing loops, and ensuring diversity and failure resilience.
Innovation Solution
A controller uses network topology information to determine and optimize P2MP LSP paths by iteratively applying link penalties and simulated annealing techniques, modifying the network topology to find the lowest total resource cost solution that accounts for routing loops, diversity, and LSP constraints, and configures the network with the best solution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional path computation methods are used for P2MP LSPs, then the network can maintain simple routing, but the resource cost increases and routing loops may occur
Solution Approach 1:
The patent modifies link metrics by applying penalties to specific links based on their usage patterns and potential to cause routing loops. By dynamically changing metric parameters, the system steers traffic away from high-cost paths and loop-prone routes, reducing overall resource consumption without requiring complex global optimization algorithms.
Solution Approach 2:
The system continuously monitors path usage and feedback from routing protocols, adjusting link penalties in real-time. This feedback mechanism allows the network to learn from actual traffic patterns and adapt path selection dynamically, optimizing resource utilization while preventing routing loops through iterative refinement.
2Reliability
If path diversity is enforced to avoid routing loops, then reliability improves, but the computational complexity increases
Solution Approach 1:
The patent segments the path computation problem into local decisions at individual links rather than global optimization. By assigning and enforcing penalties at the link level, the system achieves path diversity and loop avoidance through distributed, simple local rules rather than complex centralized algorithms, maintaining reliability while reducing computational burden.
3Reliability
If link penalties are applied to avoid routing loops, then path diversity improves, but the total resource cost may increase
Solution Approach 1:
The system applies different penalty values to different links based on their specific characteristics, usage patterns, and loop risks. Rather than uniform treatment, each link receives tailored penalties that reflect its actual contribution to routing loops versus its efficiency in carrying traffic, achieving a balance between loop avoidance and resource optimization.
Data Source
AI summary
In some examples, a controller for a network includes a path computation module configured for execution by one or more processors to obtain configuration information for at least one point-to-multipoint label switched path (P2MP LSP); obtain, from the network via at least one protocol, network topology information defining a network topology for the network; determine, based on the network topology, a first solution comprising first respective paths through the network for the at least one P2MP LSP; determine, after generating a modified network topology based on the network topology, a second solution comprising second respective paths through the network for the at least one P2MP LSP. The controller also includes a path provisioning module configured for execution by the one or more processors to configure the network with the solution of the first solution and the second solution having the lowest total cost.