Network Path Determination via Iterative Message Pruning
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Solution Overview
Problem
Conventional methods for determining the shortest path through a group of nodes require extensive computational resources and time, especially as the number of nodes increases, due to the factorial growth in computational cost, making it intractable for large networks.
Innovation Solution
A processing system iteratively provides messages to Node Processors, each representing a node, to determine paths with common endpoints, identify the lowest cost paths, and prune higher-cost paths, allowing for the identification of a target path efficiently by eliminating unnecessary calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to determine the shortest path through all nodes, then the target path can be found, but the computational cost grows factorially with the number of nodes, making it intractable for large networks
Solution Approach 1:
The patent applies preliminary action by proactively eliminating suboptimal paths early in the computational process. Before completing full path evaluations, the system identifies and prunes paths that cannot possibly lead to the optimal solution, based on partial information about path costs and node visitation patterns. This preliminary elimination dramatically reduces the search space before the main computational work begins.
Solution Approach 2:
The patent extracts and removes unnecessary computational paths from the search space. By identifying paths that share common subpaths with already-evaluated paths and determining that they cannot yield better solutions, the system extracts these redundant paths and removes them from further consideration. This extraction principle directly addresses the factorial growth problem by eliminating entire branches of the search tree.
2Measurement precision
If all possible paths are evaluated to ensure the shortest path is found, then the most accurate result is obtained, but the processing time becomes prohibitive for large numbers of nodes
Solution Approach 1:
The system performs preliminary comparisons of path costs during the messaging flow, before all paths are fully traversed. By evaluating partial path costs and comparing them against known bounds, the system can preliminarily determine that certain paths will not yield the optimal solution, eliminating the need to complete their full evaluation and thus saving computational time while maintaining accuracy.
Solution Approach 2:
The patent applies partial action by evaluating only the necessary portion of each path rather than completely traversing all possible paths. The system performs sufficient comparisons to guarantee optimality without executing redundant evaluations. This partial evaluation approach, combined with strategic pruning, achieves the required precision with significantly reduced computational effort.
3Reliability
If the system evaluates every possible path through the network, then the optimal path is guaranteed, but the processing resources required become unsustainable for large-scale networks
Solution Approach 1:
The patent extracts and removes redundant path evaluations from the computational process. By identifying paths that share common subpaths with already-evaluated paths and determining they cannot improve upon existing solutions, the system extracts these redundant computations and eliminates them. This maintains the guarantee of optimality while dramatically reducing resource consumption.
Solution Approach 2:
The system discards paths that are determined to be suboptimal during the messaging flow, rather than continuing to evaluate them. By discarding these paths early based on partial information about their cost structure, the system recovers significant processing resources that would otherwise be wasted on guaranteed suboptimal solutions, while maintaining reliability through careful pruning criteria.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, embodiments and a method. The method includes iteratively providing messages to each Node Processor. Each Node Processor represents a node of a group of nodes. The iteratively providing of the messages comprises providing first messages. Each first message includes a cost associated with a path of nodes visited by each first message. A selected path is obtained from each node having a lowest cost of a group of common endpoint costs for paths having common endpoints. A next group of messages includes the selected path. The iteratively providing of the messages results in selected paths. Also, the method include determining a target path from a remaining path. Other embodiments are disclosed.