Probabilistic Network Traffic Flow Availability Simulation
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Solution Overview
Problem
Current methods for determining network traffic flow availability fail to accurately account for the relationship between physical and logical topologies, infrastructure component failures, and shared risk link groups, leading to inaccuracies in predicting network performance and service level objectives.
Innovation Solution
A probabilistic framework using a network availability calculator that generates random failures and simulates traffic engineering scenarios to calculate the probability of fulfilling traffic demands based on cross-layer network topology models, accounting for physical and logical topologies, and considering shared risk link groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional network availability calculation methods are used, then computational speed is maintained, but measurement precision and reliability of network availability prediction deteriorate due to failure to account for physical-logical topology relationships and shared risk link groups
Solution Approach 1:
The patent segments the network model into distinct physical topology and logical topology layers, allowing independent analysis and simulation of each layer while maintaining their relationships. This segmentation enables accurate modeling of shared risk link groups by separating physical infrastructure elements from logical traffic flow elements, thereby improving measurement precision without overwhelming computational complexity.
Solution Approach 2:
The patent introduces an intermediary mapping relationship between physical and logical topologies that acts as a bridge to connect the two layers. This intermediary structure enables the simulation model to accurately track how physical failures propagate to logical traffic flows, improving prediction accuracy while maintaining a manageable model structure through the use of mapping matrices and relationship descriptors.
2Reliability
If detailed failure scenarios and cross-layer topology models are simulated, then reliability of network performance prediction improves, but loss of time for computation increases
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing the mapping relationships between physical and logical topologies, as well as pre-identifying shared risk link groups. This preliminary structuring of data allows the simulation to quickly evaluate failure scenarios without performing complex cross-layer calculations in real-time, thereby maintaining high reliability while reducing computation time during actual network availability assessment.
3Reliability
If networks are over-provisioned to ensure service level objectives, then reliability of service delivery improves, but loss of energy and resource efficiency worsens
Solution Approach 1:
The patent implements a feedback mechanism where the simulation results of network availability under various failure scenarios are fed back to the network provisioning decisions. This feedback loop enables operators to optimize network provisioning by identifying the minimum resources needed to meet service level objectives while accounting for failure risks, thereby improving reliability without unnecessary over-provisioning and reducing energy waste from underutilized resources.
Data Source
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AI summary
The present disclosure provides a probabilistic framework that can calculate the probability of fulfilling demands for a given set of traffic flows. In some implementations, the probability of fulfilling demands can be based on the probability of infrastructure component failures, shared risk link groups derived from a cross-layer network topology, and traffic engineering (TE) considerations. The consideration of the cross-layer network topology enables the systems and methods described herein to account for the relationship between the physical and logical topologies.