Adaptive Network Simulation Abstraction for Real-Time Synchronization
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Solution Overview
Problem
Conventional network simulation techniques, such as SITL, face challenges in maintaining synchronization between real-time and simulation time, leading to issues when the simulation time exceeds actual time, resulting in loss of synchronization.
Innovation Solution
A method for constructing an optimized network simulation environment involves identifying major and non-major communication equipment models, calculating abstraction priority, performing batch-mode abstraction for non-major models, driving simulations, determining real-time execution, and adapting abstraction for major models to ensure simulations are within allowable delay values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SITL technique is used to synchronize real time and simulation time, then synchronization is maintained when simulation time is shorter than actual time, but synchronization is lost when simulation time exceeds actual time
Solution Approach 1:
The patent applies dynamics by making the abstraction level of communication equipment models adaptive and changeable during simulation. The system dynamically adjusts the degree of abstraction based on real-time performance monitoring, transitioning between different levels of model fidelity to maintain synchronization. This allows the simulation to adapt its computational complexity dynamically rather than using a fixed abstraction level throughout.
Solution Approach 2:
The patent changes parameters by adjusting the abstraction level parameter of communication equipment models. When synchronization is at risk of being lost, the system increases the abstraction level (simplifying models) to reduce computation time. When synchronization margin is sufficient, the system can lower the abstraction level (increasing fidelity) to improve simulation accuracy. This parameter adjustment resolves the contradiction between maintaining synchronization and preserving model fidelity.
2Measurement precision
If high-fidelity communication equipment models are used in network simulation, then simulation accuracy is improved, but calculation time increases and real-time simulation cannot be guaranteed
Solution Approach 1:
The patent segments communication equipment models into different levels of abstraction: high-fidelity models for critical equipment that directly impacts simulation accuracy, and low-fidelity abstracted models for less critical equipment. This segmentation allows the simulation to maintain accuracy where needed while reducing overall calculation time through selective abstraction of non-critical components.
Solution Approach 2:
The patent applies local quality by assigning different abstraction levels to different communication equipment models based on their importance and impact on simulation results. Critical equipment maintains high-fidelity modeling locally, while non-critical equipment uses simplified models. This localized approach to model fidelity preserves simulation accuracy for important aspects while reducing overall computational burden.
3Reliability
If complex network models are constructed to represent real equipment accurately, then model fidelity is improved, but construction complexity and calculation time increase
Solution Approach 1:
The patent makes the model construction process dynamic by initially creating simplified abstracted models and then selectively enhancing fidelity only for critical communication equipment. This dynamic approach avoids the upfront complexity of building fully detailed models, allowing the system to start with simple constructions and add complexity only where necessary for accuracy.
Data Source
AI summary
A method of constructing an optimized network simulation environment according to the present invention includes the steps of identifying communication equipment models for relaying a message to/from real equipments out of communication equipment models within a network model, as major models, calculating the order of abstraction priority for major models, performing batch-mode abstraction for non-major models, driving a simulation, determining whether a difference between a simulation execution time and an actual time spent is within an allowable delay value, performing adaptive abstraction for the major models, and evaluating a result of the simulation. If the method according to the present invention is used, a real-time simulation having fidelity and reliability for the function and operation of real equipments can be guaranteed.