Essentials and Impact of Edge Computing in IoT Development published 10/15/2023 | 3 min read

As Internet of Things (IoT) continues to boom in potential and adoption, developers are more frequently faced with the challenge of managing and processing huge data volumes. To resolve latency issues and enhance data speed and security, edge computing has emerged as a go-to solution. In this article, we will unpack the essentials of edge computing and its growing impact on IoT development. Additionally, we'll walk through a hands-on example of deploying an edge scenario using AWS Greengrass.

Understanding Edge Computing in IoT

In edge computing, data processing happens at the edge of the source, that is, close to the IoT devices or sensors. This is unlike the traditional cloud computing model where data from the IoT devices and sensors are sent to the cloud for processing.

The key benefits edge computing brings to the IoT ecosystem include:

• Reduced Latency: By processing data at the source, edge computing significantly reduces data transport time and increases application performance.
• Increased Security: Minimizing data transmission reduces potential security vulnerabilities, offering a safer environment for sensitive data.
• Scalability: Edge computing provides easy scalability by allowing new devices and sensors to be added without the need for massive infrastructure upgrades.

AWS Greengrass: Edge Computing in Action

Amazon Web Services (AWS) offers its own edge computing solution, AWS Greengrass. To contextualize edge computing in IoT development, let's go through the simple example of gathering sensor data from an IoT device and processing it on the edge using AWS Greengrass.

To get started, here's what you'll need:

• An AWS account
• An IoT device with AWS IoT SDK installed
• An AWS Greengrass Core device (this could be a local server or an edge device)

Deploying Edge Scenario with AWS Greengrass

Here's the simplified process:

1. Configure Your Greengrass Core Device: Install the AWS Greengrass Core Software on the device you have chosen as your AWS Greengrass Core.

2. Set Up Your IoT Device: Prepare your IoT device with AWS IoT SDK and configure your device thing, certificate and policy in the AWS IoT Core.

3. Create a Greengrass Group and Add Your Core: Using the AWS Management Console, create a new Greengrass group and add your Greengrass Core to the group.

4. Deploy and Test: Deploy your Greengrass group to your core and verify that your IoT device can communicate with the Greengrass core.

  
// Sample thing Shadow update code with AWS IoT SDK
const awsIoT = require('aws-iot-device-sdk');

var thingShadow = awsIoT.thingShadow({
   keyPath: <private-key-path>,
  certPath: <certificate-path>,
    caPath: <root-CA-path>,
  clientId: <client-id>,
      host: <host-prefix>
});

thingShadow.on('connect', function() {
   console.log('Connected to AWS IoT.');
   
   var clientToken = thingShadow.update('<my-iot-device>', {
      state: {
         reported: { temperature: 22.5, humidity: 78 }
      }
   });
});

While IoT development offers exciting possibilities across many sectors, it simultaneously pushes data processing needs to a new frontier. Edge computing comes in as a savior, keeping data closer to the source, increasing processing speed, improving security, and ensuring easy scalability. As IoT grows, edge computing will undoubtedly be a crucial cog in its development wheel.

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