What is IoT Edge?
IoT Edge Meaning
The Internet-of-Things (IoT) edge is where sensors and devices communicate real-time data to a network. IoT edge computing solves latency issues associated with the cloud, as data is processed closer to its point of origin. Along with reduced latency, IoT edge architecture brings enhanced safety and a smoother end-user experience.
On a high-throughput network, such as 5G, IoT edge can be used to process large amounts of data nearly instantaneously, creating a more immersive, comprehensive experience for the user. At the same time, even when relatively small sums of data are transmitted, IoT edge can make machines and other devices that impact human safety work faster, keeping operators and others safer.
Why IoT Edge Computing is Important
Edge computing involves processing data near its source instead of sending it long distances to be processed by a remote server. This solves several important problems, many of which are associated with the latency created when data has to travel long distances.
For example, if a factory uses machines on its assembly line and their inputs are processed using a remote, cloud-based server, there could be significant safety issues. The time it takes for an input to be received by the device, get sent to the server in the cloud, processed, and then have the corresponding command sent back to the machine could be too much. If the command involves telling the machine to stop functioning because a human limb is in the way, serious injury could result.
With IoT edge, the data may only have to travel yards instead of miles, saving precious time and enhancing safety.
IoT Edge Devices
IoT edge computing depends on devices to receive, process, and output IoT data. This involves a system of connectivity dependent on devices and sensors. The data gets sent through a messaging system, processed by a computer, and then stored. Because IoT devices generate, process, and implement large amounts of data, keeping the computing process near the edge prevents latency and operational issues.
An IoT edge device is internet-enabled and typically comprised of sensors. These sensors collect data and then pass it on to the processing unit. Here, it is processed locally instead of going through the time-consuming sequence of sending it to the cloud and back. IoT devices can save network resources by collecting and processing data in a distributed fashion. In this way, workloads are spread among available devices, ensuring that none gets overworked or underutilized.
Examples of IoT Devices
Some common IoT edge devices include an IoT server, which processes data at the edge, and an IoT router, which works as an IoT hub, transmitting data to the necessary recipients. Self-driving cars are also IoT devices in that they produce, process, and use data without needing the cloud—for at least some of their processes.
Role of Machine Learning
Machine learning (ML) plays a key role in IoT edge runtime and IoT applications, and many DevOps teams include it as they design applications. ML can be used to help certain IoT edge devices understand and make predictions based on the data they store and process.
An ML application programming interface (API) can gather data from an IoT edge device and recognize patterns of inputs, user behavior, atmospheric conditions, and more. It can then predict what the next input may be and apportion the proper resources to handle it, thus reducing the amount of time it takes to process and return the data.
Going back to the example of a factory with IoT edge devices, ML can help predict what will happen next when a person crosses a certain threshold. For example, suppose the danger zone of a machine consists of a three-foot radius around it. If people continually pass by sensors within eight feet of the machine but not cross into the danger zone, ML can recognize that pattern and keep the machines functioning normally when those conditions are met.
However, if sensors are placed at four feet and the algorithm learns that 80% of the time someone who passes within four feet proceeds to cross the three-foot barrier, it can use this data to prep the machines for going offline. The same inputs can be used to set off alerts or even set up a series of safety alerts that are triggered by various distances.
Role of an IoT Gateway
An IoT gateway enables communication between devices, as well as between devices and the cloud. Its main functions include data filtering and analytics. It can also be programmed to handle the authentication of data that should be sent to cloud services, making it capable of enhancing data safety in real time, thereby improving IoT security.
If an edge agent has to communicate with another device or the cloud, the IoT gateway processes the request, clears it, and sends the information to its destination. The data that gets sent can be analyzed, and the results of the analysis can be used to identify ways to increase the efficiency of the system.
How Fortinet Can Help
Every device connected to a network is a potential attack surface. Therefore, IoT edge devices and the IoT devices they connect present novel vulnerabilities for a network. Some edge devices come with default passwords such as “admin” that customers may neglect to change to something harder to guess. Other devices are personal ones that a user may log in to and then leave open, allowing an attacker to gain access to the network. Examples include smartphones or smart cars, both of which can be stolen while the user is still logged in to the network.
However, with network access control (NAC), you can use zero-trust security architecture to block unauthorized access to a network. NAC can identify and assess IoT edge devices when they connect to a network. Each device’s credentials are then examined and verified by the system before the device is allowed to interact with the network.
FortiNAC is specifically designed to secure IoT devices. It controls their access to the network, blocking devices that may have been compromised by unauthorized individuals. FortiNAC also ensures the device complies with the network’s security protocols before allowing it to connect.
Also read more about Serverless Computing -- a cloud architecture that allows organizations to get on-demand access to the resources they need.
