Simulation of Connected Devices Memory Optimization
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Solution Overview
Problem
Existing evaluation systems for computer networks face high memory requirements due to the need to store all simulation data points, leading to inefficient resource usage as the memory usage increases with the duration and activities of simulations.
Innovation Solution
The method involves simulating device interactions by dividing transactions into individual actions, applying them to device models, and aggregating averaged latencies and device utilizations, allowing for early termination of simulations when statistical characteristics converge within a predetermined range, thus maintaining a fixed memory footprint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all simulation results data are maintained to ensure complete evaluation information, then measurement precision is improved, but memory requirements increase
Solution Approach 1:
The patent extracts only the essential evaluation metrics (latency and device utilization) from the complete simulation data, maintaining these specific measurements while discarding redundant intermediate data points. This allows evaluation accuracy to be preserved for the metrics that actually matter while dramatically reducing memory consumption by not storing all raw simulation results.
Solution Approach 2:
Instead of storing all simulation data and then analyzing it, the patent inverts the approach by continuously updating and maintaining only the aggregated evaluation metrics during simulation. This inversion allows the system to achieve complete evaluation information with minimal memory by working with summarized data throughout the simulation process rather than storing all detailed results.
2Reliability
If simulation runs for extended periods to ensure statistical convergence, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent implements feedback by continuously monitoring the stability of aggregated latency and device utilization metrics during simulation. When these metrics converge to stable values within a predetermined threshold, the simulation automatically terminates. This feedback mechanism ensures evaluation reliability through statistical convergence while minimizing simulation duration by stopping as soon as sufficient data is collected.
Solution Approach 2:
The patent makes the simulation duration dynamic rather than fixed, allowing the evaluation to continue only as long as statistical convergence is not achieved. The simulation adapts its runtime based on the actual convergence behavior of the metrics being measured, ensuring reliability without unnecessary extended running times when convergence occurs quickly.
3Measurement precision
If detailed transaction data is tracked for each action, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments transaction evaluation into distinct components (latency measurement and device utilization measurement) that are independently tracked and aggregated. This segmentation allows precise measurement of each performance aspect without requiring complex integrated data structures, as each metric can be maintained separately with simple aggregation logic.
Solution Approach 2:
The patent applies local quality by maintaining detailed measurement precision only for the specific metrics that matter (latency and device utilization) while using aggregated summaries for overall evaluation. This allows high measurement precision where needed without the complexity of tracking all possible transaction details throughout the system.
Data Source
AI summary
Simulating device interactions. A method may be practiced in a computing system for simulating interconnected devices. The method of simulating device interactions may be done in performing an overall transaction to obtain an output of system performance characteristics including measurement of latencies and/or device loads for actions performed by devices in performing the overall transaction. The method includes dividing a transaction into individual actions. The actions are applied to appropriate device models to produce latencies and/or device utilizations for the action as applied to the appropriate device model. This may be done by including an indication of an action type and optionally an action subservice. Memory resources may be conserved by ending the simulation when latencies and/or device utilizations have settled. Device utilization and latency may be aggregated and averaged over time. When changes in the latencies and/or device utilizations are within a predetermined range, the simulation can be ended.