Resource Group Function for Dynamic Path Computation
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Solution Overview
Problem
Current resource information models in networks, such as those used in WDM networks, fail to account for relationships between resources, leading to sub-optimal or incomplete path computations due to treating resources as individual and unrelated entities, which is problematic in time-critical environments.
Innovation Solution
A method that derives a resource group function from relationships among network resources to form network resource groups, allowing for dynamic resource-level path computation that accounts for these relationships, which can be automatically or manually generated and used to control resources based on traffic engineering goals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If resources are treated as individual and unrelated entities in path computation, then the computation process is simpler, but the results are incomplete and sub-optimal
Solution Approach 1:
The patent merges individual resources that share common attributes, functionalities, and inter-relationships into resource groups. This grouping approach allows the path computation to consider relationships between resources while maintaining computational efficiency. The resource group function captures the collective behavior of grouped resources, enabling complete and optimal path computation without treating each resource as entirely independent.
Solution Approach 2:
The patent introduces a new parameter dimension by adding resource group functions to the traditional resource information model. This parameter change enables the computation to account for resource relationships without fundamentally redesigning the entire model. The resource group function serves as an additional layer of information that enriches the path computation capability while maintaining compatibility with existing computational frameworks.
2Productivity
If heuristic-based procedures are used for path computation, then the computation can be executed, but the results are sub-optimal and may require exhaustive searches
Solution Approach 1:
The patent performs preliminary action by pre-defining resource groups and their associated functions based on shared attributes and relationships. This pre-processing step organizes resource information in a structured manner before path computation begins, enabling the algorithm to efficiently query and utilize resource relationships without performing exhaustive searches during the actual path computation process.
Solution Approach 2:
The resource group function serves as an intermediary between individual resources and the path computation algorithm. Instead of directly processing complex relationships between individual resources, the algorithm interacts with the resource group function, which encapsulates the relationship information. This intermediary structure simplifies the computation process while ensuring complete and optimal results.
3Reliability
If current resource information models are used, then the model structure is simple, but applications cannot generate computationally complete results
Solution Approach 1:
The patent segments the resource information model into two distinct components: individual resource attributes and resource group functions. This segmentation allows the model to maintain simplicity at the individual resource level while adding relationship information through separate group function definitions. The modular structure enables applications to query only the necessary information for their specific needs, achieving computational completeness without overwhelming complexity.
Solution Approach 2:
The resource group function serves multiple purposes: it captures resource relationships, enables efficient querying, and provides a unified interface for path computation. This multi-functional design allows a single addition to the information model to address multiple requirements simultaneously, improving reliability without proportionally increasing complexity.
Data Source
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AI summary
A method for complementing dynamic resource-level path computation with a resource grouping constraint in a network comprising the steps of deriving a resource group function, RGF, from relationships amongst network resources within at least one network element forming at least one network resource group, NRG, and performing the resource-level path computation accounting for the derived resource group function, RGF.