Optimize your IoT Services for Scale with IoT Device Simulator

The IoT (Internet of Things) has accelerated digital transformation for many industries. Companies can now offer smarter home devices, remote patient monitoring, connected and autonomous vehicles, smart consumer devices, and many more products. The enormous volume of data emitted from IoT devices can be used to improve performance, efficiency, and develop new service and business models. This can help you build better relationships with your end consumers. But you’ll need an efficient and affordable way to test your IoT backend services without incurring significant capex by deploying test devices to generate this data.

IoT Device Simulator (IDS) is an AWS Solution that manufacturing companies can use to simulate data, test device integration, and improve the performance of their IoT backend services. The solution enables you to create hundreds of IoT devices with unique attributes and properties. You can simulate data without configuring and managing physical devices.

An intuitive UI to create and manage devices and simulations

IoT Device Simulator comes with an intuitive user interface that enables you to create and manage device types for data simulation. The solution also provides you with a pre-built autonomous car device type to simulate a fleet of connected vehicles. Once you create devices, you can create simulations and generate data (see Figure 1.)

Figure 1. The landing page UI enables you to create devices and simulation

Create devices and simulate data

With IDS, you can create multiple device types with varying properties and data attributes (see Figure 2.) Each device type has a topic where simulation data is sent. The supported data types are object, array, sinusoidal, location, Boolean, integer, float, and more. Refer to this full list of data types. Additionally, you can import device types via a specific JSON format or use the existing automotive demo to pre-populate connected vehicles.

Figure 2. Create multiple device types and their data attributes

Create and manage simulations

With IDS, you can create simulations with one device or multiple device types (see Figure 3.) In addition, you can specify the number of devices to simulate for each device type and how often data is generated and sent.

Figure 3. Create simulations for multiple devices

You can then run multiple simulations (see Figure 4) and use the data generated to test your IoT backend services and infrastructure. In addition, you have the flexibility to stop and restart the simulation as needed.

Figure 4. Run and stop multiple simulations

You can view the simulation in real time and observe the data messages flowing through. This way you can ensure that the simulation is working as expected (see Figure 5.) You can stop the simulation or add a new simulation to the mix at any time.

Figure 5. Observe your simulation in real time

IoT Device Simulator architecture

Figure 6. IoT Device Simulator architecture

The AWS CloudFormation template for this solution deploys the following architecture, shown in Figure 6:

1. Amazon CloudFront serves the web interface content from an Amazon Simple Storage Service (Amazon S3) bucket.
2. The Amazon S3 bucket hosts the web interface.
3. Amazon Cognito user pool authenticates the API requests.
4. An Amazon API Gateway API provides the solution’s API layer.
5. AWS Lambda serves as the solution’s microservices and routes API requests.
6. Amazon DynamoDB stores simulation and device type information.
7. AWS Step Functions include an AWS Lambda simulator function to simulate devices and send messages.
8. An Amazon S3 bucket stores pre-defined routes that are used for the automotive demo (which is a pre-built example in the solution).
9. AWS IoT Core serves as the endpoint to which messages are sent.
10. Amazon Location Service provides the map display showing the location of automotive devices for the automotive demo.

The IoT Device Simulator console is hosted on an Amazon S3 bucket, which is accessed via Amazon CloudFront. It uses Amazon Cognito to manage access. API calls, such as retrieving or manipulating information from the databases or running simulations, are routed through API Gateway. API Gateway calls the microservices, which will call the relevant service.

For example, when creating a new device type, the request is sent to API Gateway, which then routes the request to the microservices Lambda function. Based on the request, the microservices Lambda function recognizes that it is a request to create a device type and saves the device type to DynamoDB.

Running a simulation

When running a simulation, the microservices Lambda starts a Step Functions workflow. First, the request contains information about the simulation to be run, including the unique device type ID. Then, using the unique device type ID, Step Functions retrieves all the necessary information about each device type to run the simulation. Once all the information has been retrieved, the simulator Lambda function is run. The simulator Lambda function uses the device type information, including the message payload template. The Lambda function uses this template to build the message sent to the IoT topic specified for the device type.

When running a custom device type, the simulator generates random information based on the values provided for each attribute. For example, when the automotive simulation is run, the simulation runs a series of calculations to simulate an automobile moving along a series of pre-defined routes. Pre-defined routes are created and stored in an S3 bucket, when the solution is launched. The simulation retrieves the routes at random each time the Lambda function runs. Automotive demo simulations also show a map generated from Amazon Location Service and display the device locations as they move.

The simulator exits once the Lambda function has completed or has reached the fifteen-minute execution limit. It then passes all the necessary information back to the Step Function. Step Functions then enters a choice state and restarts the Lambda function if it has not yet surpassed the duration specified for the simulation. It then passes all the pertinent information back to the Lambda function so that it can resume where it left off. The simulator Lambda function also checks DynamoDB every thirty seconds to see if the user has manually stopped the simulation. If it has, it will end the simulation early. Once the simulation is complete, the Step Function updates the DynamoDB table.

The solution enables you to launch hundreds of devices to test backend infrastructure in an IoT workflow. The solution contains an Import/Export feature to share device types. Exporting a device type generates a JSON file that represents the device type. The JSON file can then be imported to create the same device type automatically. The solution allows the viewing of up to 100 messages while the solution is running. You can also filter the messages by topic and device and see what data each device emits.

Conclusion

IoT Device Simulator is designed to help customers test device integration and IoT backend services more efficiently without incurring capex for physical devices. This solution provides an intuitive web-based graphic user interface (GUI) that enables customers to create and simulate hundreds of connected devices. It is not necessary to configure and manage physical devices or develop time-consuming scripts. Although we’ve illustrated an automotive application in this post, this simulator can be used for many different industries, such as consumer electronics, healthcare equipment, utilities, manufacturing, and more.

Get started with IoT Device Simulator today.