Resilient Network Routing via Genetic Non-Intersecting Path Optimization
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Solution Overview
Problem
Existing route-finding techniques, such as Dijkstra's algorithm, are inadequate for determining multiple non-intersecting primary and secondary routes in communications networks, leading to increased resource costs and potential single points of failure due to their greedy nature, which prioritizes the lowest cost route without considering subsequent routes.
Innovation Solution
A hybrid method combining a greedy route-finding algorithm with a genetic algorithm to iteratively identify and optimize non-intersecting primary and secondary routes by defining a population set, applying mutation and crossover, and selecting routes with the lowest aggregate edge weights, ensuring no shared nodes or edges between the routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a greedy route-finding algorithm is used to determine the shortest route, then the primary route has minimal resource usage, but the secondary route cannot be completely independent of the primary route
Solution Approach 1:
The patent segments the route determination process into two distinct phases: first determining the primary route using a greedy algorithm for minimal resource usage, then determining the secondary route by excluding edges from the primary route to ensure independence. This segmentation allows both routes to optimize for their respective goals without conflict.
Solution Approach 2:
The patent applies preliminary action by first establishing the primary route before determining the secondary route. By pre-defining which edges are used in the primary route and excluding them from consideration for the secondary route, the system ensures complete route independence while maintaining resource efficiency in the primary path.
2Reliability
If multiple independent routes are provided for backup, then network resilience is improved, but the complexity of determining and maintaining these routes increases
Solution Approach 1:
The system performs preliminary determination of both primary and secondary routes during network setup or planning phases. By pre-calculating and storing these routes before failures occur, the system reduces real-time complexity while maintaining high resilience. The exclusion of primary route edges from secondary route consideration is performed in advance.
Solution Approach 2:
The patent creates a modified copy of the network graph for secondary route determination, where edges used in the primary route are excluded. This copying approach simplifies the complexity by providing a pre-prepared alternative graph structure that automatically enforces route independence without requiring complex real-time calculations.
3Reliability
If the secondary route excludes all edges from the primary route, then complete route independence is achieved, but the resource cost of the secondary route increases
Solution Approach 1:
The patent segments the edge set into two distinct groups: edges available for the primary route and edges reserved for the secondary route. By excluding only the specific edges used in the primary route from the secondary route consideration, the system achieves complete independence while allowing the secondary route to utilize other available edges, thus minimizing resource cost increase.
Solution Approach 2:
The patent changes the parameter space for secondary route determination by excluding specific edges from the primary route. This parameter modification allows the secondary route algorithm to search for the optimal path within the remaining edges, minimizing resource cost while ensuring complete independence from the primary route.
Data Source
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AI summary
A computer implemented method of determining non-intersecting primary and secondary routes between source and destination nodes in a communications network represented by a graph data structure of nodes and edges, edges having associated a weight corresponding to a resource involved in traversing the edge, the method comprising: defining a population set of primary routes based on at least one initial primary route between the source and the destination nodes and at least one additional primary route defined based on a mutation of the initial primary route, wherein the initial primary route is determined by a greedy route-finding algorithm, and wherein each primary route in the population set identifies a secondary route based on the greedy route-finding algorithm applied to the graph having edges in the primary route excluded from the graph, such that the primary and secondary routes are non-intersecting routes through the graph; applying a genetic algorithm to the population set to iteratively select and crossover pairs of primary routes in the sorted population set, the genetic algorithm being applied until a stopping condition is reached, wherein at least a subset of the selected primary routes are mutated in the population set; and selecting, from the population set, a primary route and corresponding secondary route having a lowest aggregate weight of edges.