IoT Device Virtualization via Doppel Models for Testing
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Solution Overview
Problem
The complexity of IoT applications due to diverse and heterogeneous devices, unreliable networks, and real-world interactions poses significant challenges in testing, making traditional testing methods inadequate for ensuring reliability and scalability.
Innovation Solution
A system that models virtualized instances of physical devices (Doppel Models) and generates data doubles to simulate real-world scenarios, including faulty data and network patterns, allowing for comprehensive testing of IoT applications without relying on physical devices or frequent access to real environments, using a low-code platform integrated with cloud-based services and standard CI/CD platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional testing methods are used for IoT applications, then the testing process is simpler, but the reliability and scalability of IoT applications cannot be ensured due to diverse devices, unreliable networks, and real-world interactions
Solution Approach 1:
The patent creates virtual copies (Doppel Models) of physical IoT devices that replicate their data generation behavior, network communication patterns, and operational characteristics. These digital twins enable comprehensive testing of IoT applications without requiring actual physical devices, thereby ensuring reliability while managing complexity through virtualization.
Solution Approach 2:
The system allows dynamic modification of device parameters, data streams, and network conditions in the virtual models. Testers can change parameters such as device states, sensor readings, network latency, and packet loss rates to simulate various real-world scenarios, enabling thorough reliability testing without physical device complexity.
2Productivity
If physical devices are used for testing, then realistic device behavior can be obtained, but dependency on physical devices and frequent access to real environments is required
Solution Approach 1:
Virtual device models serve as substitutes for physical devices, eliminating the need for frequent access to real test environments. The Doppel Models capture essential device behaviors and data patterns, allowing developers to conduct comprehensive testing in controlled virtual environments, thereby accelerating development productivity without sacrificing operational ease.
Solution Approach 2:
The system pre-configures virtual device models with realistic device behaviors, data generation patterns, and network characteristics before testing begins. This preliminary setup includes capturing actual device data streams and replicating their temporal and statistical properties, so that when testing occurs, realistic scenarios are already in place without requiring physical device access.
3Reliability
If comprehensive test scenarios including faulty data and network patterns are simulated, then testing coverage is improved, but the complexity of defining and managing test conditions increases
Solution Approach 1:
The system copies real device behaviors and network patterns into virtual models, including fault conditions and anomalous data streams. By replicating actual device failure modes and network issues in the Doppel Models, comprehensive testing coverage is achieved while the virtualization framework manages the complexity of defining and managing these diverse test conditions.
Solution Approach 2:
The virtual device model framework provides universal capabilities for simulating various device types, network conditions, and fault scenarios through a unified interface. The Doppel Models can represent different device categories (sensors, actuators, gateways) and test conditions (normal operation, faults, network issues) using consistent modeling approaches, reducing test suite complexity while maintaining comprehensive coverage.
Data Source
AI summary
Described herein is a system for device virtualization and simulation of the behaviour of a system of things for testing IoT applications. The aforementioned system comprises a modelling engine, a test suite designer, a simulation engine, and a reporting engine. The modelling engine defines the attributes, data transfer protocols and normal data behaviour of any physical device, and for defining virtual devices that can co-exist with actual devices and can be used to simulate both the things themselves as well as the gateway and the network. The test suite designer defines the device data behaviour under various test conditions. The simulation engine generates test data streams for various test scenarios as required by the software tester. The reporting engine generates various types of test reports.