Traffic Pattern Model Comparison for Complex Communication Systems
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Solution Overview
Problem
Legacy telecommunications networks are inadequate to meet current demands due to their complexity and inability to effectively manage the combination of voice and data traffic, requiring improved methods for modeling and optimizing traffic patterns.
Innovation Solution
A method and system for comparing traffic pattern models in complex communication systems by computing normalized transmission parameters and model parameters, allowing for the comparison of anticipated and actual traffic flow, which helps in identifying optimal capacity requirements and service levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If legacy telecommunications networks are used to manage traffic, then network architecture is simple, but the network is inadequate to meet current demands for voice and data combination
Solution Approach 1:
The patent segments the complex communication system into multiple subsystems, each with its own traffic pattern model. By dividing the network into manageable components (different traffic types, time periods, and patterns), the system can handle complex voice and data combinations while maintaining model simplicity through modular analysis of each segment separately.
2Measurement precision
If multiple traffic pattern models are used to represent complex traffic flows, then traffic modeling accuracy is improved, but model complexity increases
Solution Approach 1:
The patent transforms complex traffic pattern models into comparable forms by computing normalized transmission parameters and model parameters. This parameter transformation allows different complex models (representing various traffic flows, times, and patterns) to be systematically compared and evaluated, maintaining modeling accuracy while enabling simplified comparison through standardized parameter metrics.
3Reliability
If traditional network capacity planning is used, then capital expenditures are high, but service quality cannot be compromised
Solution Approach 1:
The patent implements a feedback mechanism by comparing model parameters representing anticipated traffic patterns with actual traffic flow data. This comparison allows the system to validate traffic models against real-world performance, ensuring that capacity planning decisions are based on accurate predictions that maintain service quality while optimizing resource allocation and reducing unnecessary capacity requirements.
Data Source
AI summary
Traffic pattern models of a complex communication system are compared. A normalized transmission parameter is computed for each traffic pattern model. Model parameters are also computed for each traffic pattern model. The model parameters for each traffic pattern model represent anticipated traffic flow through the complex communication system over a predetermined time period. Data representing an actual traffic flow pattern through the complex communication system over the predetermined time period is compared to the model parameters representing anticipated traffic patterns for each model. The normalized transmission parameters for each of the traffic pattern models are also compared.