Traffic Flow Optimization via Constraint-Based Bounds
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Solution Overview
Problem
Current traffic flow optimization systems in communications networks face challenges in accurately calculating traffic values for modified scenarios without complete end-to-end traffic loads, leading to inconsistent estimates and resource utilization imbalances.
Innovation Solution
A method that calculates traffic values in communications networks by obtaining traffic data measurements from initial scenarios, deriving constraints for interdependency, and using these to calculate upper and lower bounds for modified scenarios, allowing for accurate and reliable traffic value estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If discrete event simulation is used for network planning, then network optimization capability is improved, but complete end-to-end traffic load data is required which increases system complexity and cost
Solution Approach 1:
The patent extracts only the necessary traffic flow relationships and constraints from the complete end-to-end traffic load data. Instead of requiring full traffic matrices, the system derives flow relationships from partial link traffic measurements, extracting minimal sufficient information for optimization purposes.
Solution Approach 2:
The patent introduces an intermediary mathematical model that connects partial traffic measurements to optimization objectives. This model acts as a mediator between incomplete data and the optimization algorithm, enabling planning without direct access to complete end-to-end traffic loads.
2Measurement precision
If traffic data is collected using probes or router-based information, then traffic measurement accuracy is improved, but implementation cost increases and network congestion worsens
Solution Approach 1:
The patent enables the network to self-measure traffic flows using existing link traffic counters that are already present in network devices. The system utilizes automatically generated traffic data from network operations itself, eliminating the need for external probes or additional measurement infrastructure.
3Quantity of substance
If discrete event simulation with estimated data is used, then implementation cost is reduced, but traffic flow estimation consistency deteriorates
Solution Approach 1:
The patent incorporates feedback mechanisms through mathematical constraints that ensure consistency between estimated traffic flows and observed link measurements. The optimization model continuously adjusts flow estimates to satisfy flow conservation and non-negativity constraints, maintaining reliability without requiring expensive complete data collection.
Data Source
AI summary
A method of calculating traffic values in a communications network (1), the communications network comprising a plurality of nodes (2,4), the nodes being connected to one another by links (24), the method comprising: (a) obtaining traffic data measurements (102) through said nodes and/or links in an initial scenario as input data; (b) deriving a traffic flow model for a modified scenario using a plurality of constraints describing the interdependency of said initial to said modified scenario (116); and (c) calculating values and/or upper and lower bounds of traffic values for said modified scenario from said traffic flow model using said input data (118).