Resource-Oriented Dependency Graph for Network Configuration
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Solution Overview
Problem
Communication networks face challenges in dynamically managing resource demands and network topology changes, leading to suboptimal resource utilization and potential deadlocks due to unmanaged dependency cycles.
Innovation Solution
A method and apparatus for constructing and analyzing resource-oriented dependency graphs, which determine initial and new resource demands, apply policies for demand assignment, create sub-graphs, and incorporate them into a resource-oriented dependency graph to identify and break dependency cycles, thereby rerouting demands for improved resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network resources are dynamically allocated to meet changing demands, then network adaptability and resource utilization are improved, but dependency cycles may form causing deadlocks and system failures
Solution Approach 1:
The patent applies preliminary action by detecting dependency cycles in the resource allocation graph before deadlocks occur. The system continuously monitors resource demands and allocations, identifies potential cyclic dependencies, and breaks them proactively by selecting demands to disrupt, preventing deadlocks before they can form and maintain system reliability while allowing dynamic resource allocation
Solution Approach 2:
The patent implements feedback by continuously monitoring the resource allocation graph for dependency cycles and using this information to dynamically adjust resource allocation decisions. The system feeds back cycle detection results to the resource allocation mechanism, which then modifies allocation to break cycles, creating a closed-loop control system that maintains reliability during dynamic adaptation
2Reliability
If resource allocation policies are strictly enforced to prevent deadlocks, then system reliability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent applies partial action by implementing selective deadlock prevention rather than universal restrictions. Instead of enforcing rigid allocation policies on all resources, the system only intervenes when dependency cycles are detected, allowing flexible resource allocation for non-critical resources while applying constraints only where necessary to break cycles, thus maintaining high utilization efficiency while ensuring reliability
Solution Approach 2:
The patent changes the parameter of resource allocation from static policy-based to dynamic graph-based control. By representing resource allocation as a graph structure and dynamically adjusting allocation decisions based on graph analysis (cycle detection and breaking), the system adapts allocation parameters in real-time to prevent deadlocks while maximizing resource utilization, rather than relying on fixed conservative policies
3Productivity
If the network topology is frequently reconfigured to optimize performance, then network productivity is improved, but the complexity of managing resource dependencies increases
Solution Approach 1:
The patent introduces an intermediary resource allocation graph that mediates between network topology changes and resource allocation decisions. This graph structure serves as an intermediate representation that simplifies dependency tracking by explicitly modeling resource demands, allocations, and dependencies, making it easier to manage complexity during frequent topology reconfigurations while maintaining high network productivity
Data Source
AI summary
A method for network analysis includes determining an initial set of demands upon the resources of a network, determining a new set of demands upon the resources of the network, apply a policy for assigning a demand of the new set of demands to a demand of the initial set of demands, create a dependency for the assignment of the demand of the new set of demands to the demand of the initial set of demands, construct a sub-graph including the dependency, and incorporate the sub-graph into a resource-oriented-dependency graph. Each demand includes a quantification.