Disjoint Path Computation in Optical Networks
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Solution Overview
Problem
Existing disjoint path computation algorithms, such as Suurballe's algorithm, fail to provide feasible or optimal solutions for spectrum continuity constraints in optical networks, leading to inefficient and computationally complex iterations, especially in DWDM networks with wavelength continuity constraints.
Innovation Solution
A modified approach that initializes variables for a graph representing the network, determines a first path, and then uses an auxiliary directed graph to find a second path by considering entry and exit from cut edges and adjusting variables to address continuity constraints, applying Shortest Path First (SPF) and modifying weights to ensure spectrum continuity, with the option to reiterate if no solution is found.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Suurballe's algorithm is applied to find disjoint paths in optical networks, then two separate paths can be determined, but the algorithm fails to provide feasible or optimal solutions for spectrum continuity constraints
Solution Approach 1:
The patent segments the path computation process into two distinct phases: first computing a primary path using modified Suurballe's algorithm, then computing a secondary path while explicitly considering spectrum continuity constraints. This segmentation allows each phase to focus on specific requirements, with the secondary path computation ensuring wavelength continuity is maintained.
Solution Approach 2:
The patent introduces an intermediary data structure (wavelength availability matrix and path state tracking) that mediates between the disjoint path requirement and spectrum continuity constraint. This intermediary mechanism tracks wavelength usage along the primary path and uses this information to guide secondary path computation, ensuring both objectives are met.
2Manufacturing precision
If the network is divided into multiple networks for each wavelength to evaluate optimal solutions, then spectrum continuity can be ensured, but the computational complexity increases significantly with high-performance penalty
Solution Approach 1:
Instead of dividing the network into 128 separate networks for each wavelength (excessive action), the patent applies partial action by only considering wavelength availability along the specific primary path computed. This selective approach evaluates spectrum continuity only where needed, reducing computational complexity from O(128×128) to a manageable level while still ensuring constraint satisfaction.
Solution Approach 2:
The patent applies local quality by focusing spectrum continuity checks specifically on the alternating path segments between the primary and secondary paths, rather than uniformly applying constraints across the entire network. This localized approach ensures computational efficiency while maintaining constraint satisfaction in critical areas.
3Manufacturing precision
If spectrum continuity constraints are applied in gridless networks with continuous spectral range, then optimal solutions can be found, but no solution is found due to the continuous spectral range without any grid slots
Solution Approach 1:
The patent changes the parameter representation from continuous spectral ranges to discrete wavelength indices along the computed path. By tracking wavelength availability as a discrete sequence along the primary path and using this to guide secondary path computation, the algorithm makes gridless network problems computationally feasible while still optimizing spectrum assignment.
Data Source
AI summary
Systems and methods for computing disjoint paths in a network considering continuity constraints include, responsive to a request for disjoint paths in the network which are subject to the continuity constraints, initializing a plurality of variables associated with a graph defining the network where edges constitute nodes and vertices constitute links; determining a first path through the graph; determining an auxiliary directed graph based on the first path; and determining a second path through the auxiliary directed graph, wherein the second path is determined by considering entry into cut edges, exit from cut edges, and a destination in the auxiliary directed graph and the plurality of variables are adjusted based on the entry, the exit, and the destination to address the continuity constraints. This approach concept applies to not just continuity constraints but to any constraints, which are non-additive in nature; the objective function is still additive for Shortest Path First (SPF).