IoT Solution Sizing via Hybrid Simulation
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Solution Overview
Problem
The complexity of IoT edge system infrastructure sizing due to interdependent characteristics like transport protocols, sensor receive and actuation characteristics, and I/O channels leads to suboptimal solution offerings, with linear extrapolations failing to represent real-world measurements, resulting in increased costs and delayed market adoption.
Innovation Solution
The implementation of interfaces and procedures for sensors, simulators, and system models that facilitate optimal IoT solution sizing by determining the impact of input parameters, using a hybrid architecture of live and simulated components to simulate various workloads and configurations, thereby reducing the complexity of solution sizing and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If linear extrapolations are used to estimate solution sizing, then the process is simple and quick, but the accuracy represents real-world measurements is poor
Solution Approach 1:
The patent creates virtual copies of physical IoT devices and network infrastructure through simulation. These simulated components replicate real-world behavior without requiring actual hardware deployments, enabling accurate measurement of solution sizing impacts while avoiding the complexity of physical testing across multiple configurations
Solution Approach 2:
The system varies key parameters such as number of devices, data transmission rates, network topology configurations, and workload patterns to create multiple simulation scenarios. By systematically changing these parameters and measuring outcomes, the system builds accurate predictive models for solution sizing without requiring physical infrastructure for each scenario
2Measurement precision
If comprehensive simulations of all permutations are conducted, then the accuracy of solution sizing is improved, but the time required for evaluation increases
Solution Approach 1:
The patent divides the complex evaluation space into discrete, manageable simulation scenarios based on key parameters and constraints. Instead of simulating all possible permutations exhaustively, the system segments the problem into representative cases that capture essential behaviors, then uses these results to extrapolate to broader scenarios efficiently
Solution Approach 2:
The system performs targeted simulations of the most critical and varied scenarios rather than all possible configurations. By identifying and simulating the most impactful parameter combinations (partial action), the system achieves sufficient accuracy without the time cost of exhaustive testing (excessive action)
3Reliability
If multiple real-world deployments are tested, then the reliability of solution sizing is improved, but the cost increases
Solution Approach 1:
The patent creates virtual replicas of physical IoT deployments that replicate network behavior, device interactions, and performance characteristics without requiring actual hardware. These simulated deployments provide reliable data for solution sizing validation while eliminating the financial cost of physical infrastructure, devices, and deployment operations
Data Source
AI summary
The techniques disclosed herein include a computing device for Internet of Things (IoT) solution sizing. The computing device is to determine a solution deployment metric, trigger edge traffic, monitor a round trip characteristic and an actuation pattern, execute permutations of input workloads, and determine a solution deployment.