Intelligent Agents for Telecommunications Flow Path Discovery
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Solution Overview
Problem
Existing communication network path selection methods are inefficient and inflexible, particularly in handling changing network dynamics, and are processor-intensive, making them slow and unsuitable for optimizing flow path assignments for signaling and media traffic.
Innovation Solution
The implementation of intelligent agents at each communication component to propagate signals, determine acceptance or refusal based on signal properties and network conditions, and record propagation states in a tree structure to optimize flow path discovery and assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network graph propagation methods are used to select network path flows, then path selection can be performed based on given constraints, but the methods are slow due to the NP-complete nature of the discovery process
Solution Approach 1:
The patent segments the path discovery process by deploying intelligent agents at individual network components rather than using centralized graph propagation. Each component independently evaluates incoming signals and makes local acceptance/refusal decisions, dividing the complex NP-complete problem into manageable distributed units that operate in parallel.
Solution Approach 2:
Each network component is equipped with an intelligent agent that autonomously evaluates signals and makes decisions about acceptance and forwarding without requiring centralized control or complex global path calculations. The agents self-manage the path selection process locally, eliminating the need for processor-intensive centralized optimization.
2Adaptability or versatility
If traditional path selection methods are used, then path routing can be determined, but the methods are processor intensive and inflexible to changing network dynamics
Solution Approach 1:
The patent implements dynamic path selection where intelligent agents continuously evaluate incoming signals against current network conditions and component properties. The system adapts in real-time to changing dynamics such as load, component failure rates, and network topology changes without requiring re-computation of global paths, making the routing flexible and responsive.
Solution Approach 2:
Each component's intelligent agent independently and continuously monitors its own state and makes real-time decisions about signal acceptance and forwarding based on current network conditions. This distributed self-service approach eliminates the need for processor-intensive centralized optimization while maintaining adaptability to dynamic changes.
3Loss of information
If signal propagation is performed through all components, then complete path discovery can be achieved, but the process requires extensive processing and time
Solution Approach 1:
The patent records the state of signal propagation in a tree structure as signals traverse the network, enabling preliminary evaluation and pruning of paths. This allows the system to maintain complete path information while reducing discovery time by avoiding redundant evaluations and efficiently managing the exploration of multiple potential paths through structured recording.
Data Source
AI summary
The present invention provides methods, devices, and systems for modeling optimized flow path assignments for signaling and media traffic in a network connected population of telecommunications systems. More specifically, optimum inter- and intra-system flow path assignments can be determined based on, for example, a virtual simulation of the telecommunications system. The optimization criteria may include flow path properties, flow path length, flow path element degradation of voice quality, monetary cost of flow path element usage, and flow path element contribution to overall system availability.