WDM Optical Network Path Planning Optimization
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Solution Overview
Problem
Current network planning methods for WDM optical networks are complex and computationally intensive, often resulting in suboptimal solutions due to the prohibition of loops, which hinders efficient resource utilization and increases costs.
Innovation Solution
A method that includes an initial routing step to allocate loopless network paths and an optimization step to re-allocate traffic demands among candidate optical connections, focusing on minimizing the number of WDM transponders by selecting connections based on low used-capacity or high free-capacity criteria, while allowing for looped paths to reduce network resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If loopless paths are enforced in path computation, then computational complexity is reduced and convergence is improved, but solution optimality deteriorates due to suboptimal connection maps
Solution Approach 1:
The path computation process is divided into two distinct phases: an initial routing step that enforces loopless paths for computational efficiency, and a subsequent optimization step that relaxes the loopless constraint to improve solution optimality. This segmentation allows each phase to focus on its specific objective without compromising the other.
Solution Approach 2:
The initial routing step performs a preliminary allocation of loopless paths before the optimization step. This preliminary action establishes a feasible baseline solution that ensures computational convergence, which is then refined in the optimization phase to achieve better optimality.
2Manufacturing precision
If comprehensive multilayer network design optimization is performed, then network cost reduction is improved, but computational complexity increases significantly
Solution Approach 1:
The comprehensive network design optimization problem is segmented into multiple manageable steps: initial routing with loopless constraints, candidate optical connection definition, and iterative optimization. This segmentation reduces the computational burden of each individual step while maintaining overall optimization effectiveness.
Solution Approach 2:
The optimization process dynamically adjusts the set of candidate optical connections during iterative steps, withdrawing connections that are no longer optimal and adding new candidates. This dynamic approach allows the system to converge to optimal solutions without requiring exhaustive computation of all possible configurations.
3Manufacturing precision
If the number of candidate optical connections is increased, then solution optimality is improved, but computational time increases
Solution Approach 1:
The set of candidate optical connections is dynamically managed through iterative withdrawal and addition of connections based on optimization criteria. This dynamic adjustment allows the algorithm to focus computational resources on the most promising candidates, achieving good optimality without exhaustively evaluating all possible connections.
Solution Approach 2:
The algorithm considers a sufficient number of candidate connections to achieve near-optimal solutions without evaluating every possible connection. By using optimization criteria to selectively withdraw and add connections, the system achieves practical optimality within reasonable computational time limits.
Data Source
AI summary
An exemplary technique is provided for planning a plurality of optical connections as a function of a plurality of traffic demand. In a routing step, a loopless network path is allocated to each traffic demand. Each traffic demand is allocated to a candidate optical connection or chain of candidate optical connections selected to carry the capacity of the traffic demand along the loopless network path allocated to the traffic demand. In an optimization step, a reduced set of candidate optical connections is defined by withdrawing the candidate optical connection to be withdrawn. A candidate optical connection or a chain of candidate optical connections is determined to be re-used among the reduced set of candidate optical connections. The traffic demand is re-allocated to the candidate optical connection or chain of candidate optical connections to be re-used.