Network Model Equivalence Testing via Normal Form Simplification
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Solution Overview
Problem
Current network modeling techniques, such as NetML, do not provide mechanisms for automatically comparing or determining the equivalence and generalization of network models, which is essential for understanding the complex layered nature of telecommunications networks.
Innovation Solution
The method involves obtaining models of networks, simplifying them using normal form rules, and performing equivalence tests to determine if the simplified models are isomorphic, with additional rules for handling reverse multiplexing and adaptation, allowing for the determination of equivalence and generalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If network models are simplified using normal form rules, then the complexity of equivalence testing is reduced, but the precision of model representation may be lost
Solution Approach 1:
The equivalence testing process is segmented into two distinct phases: first, simplifying network models using normal form rules to reduce complexity, and second, performing equivalence testing on the simplified models. This segmentation allows the system to manage complex network models by breaking down the equivalence verification into manageable steps, reducing the overall computational complexity while maintaining verification capability.
Solution Approach 2:
The patent creates simplified copies of network models through normal form transformations. These copied models retain the essential structural characteristics needed for equivalence testing while eliminating redundant elements. The copying approach enables equivalence verification without requiring direct comparison of the full, complex original models, thus reducing computational burden.
2Measurement precision
If equivalence testing is performed on detailed network models, then measurement precision is improved, but the time required for testing increases
Solution Approach 1:
The patent applies preliminary action by performing normal form simplification on network models before conducting equivalence testing. This preprocessing step transforms complex models into simplified representations that retain essential equivalence characteristics. By preparing the models in advance through simplification, the actual equivalence testing phase requires less computational time while maintaining sufficient accuracy for determining network equivalence.
3Ease of operation
If normal form rules are applied to simplify network models, then the ease of operation for equivalence testing is improved, but the device complexity increases due to additional transformation rules
Solution Approach 1:
The normal form transformation rules are designed to be self-applying to network models. The simplification process automatically transforms complex network representations into standardized normal forms without requiring manual intervention or complex external processing. This self-service characteristic of the transformation rules makes the equivalence testing process easier to operate, as the system autonomously handles the simplification step before testing.
Data Source
AI summary
Methods and apparatus are provided for determining equivalence and generalization of a network model. A method is provided for determining whether two networks are equivalent. A model of at least two networks is obtained, and then simplified using one or more normal form rules. A test is then performed to determine if the two simplified network models are equivalent (e.g., isomorphic). A first network M is said to be generalized by a second network N, M≦N, if every test that satisfies M also satisfies N. A first network M is said to be equivalent to a second network N, N≡M, if M generalizes N and N generalizes M.