If you are into the internet of things and – in particular – Industrial Internet of Things you may have heard the term edge computing being thrown around. What is edge computing really? Let me dial it down a bit and start from the basics;
IoT (Internet of Things)
Internet of things describes physical objects with sensors, processing ability, software and other technology that connect and exchange data with other devices and systems over a communication network.
From a more technical standpoint, it describes the network of physical devices that are embedded with sensors, software and other technologies for the purpose of connecting and exchanging data (data communications) with other devices and systems over the internet.
The range of these devices is immense, covering anything from simple household objects to sophisticated industrial tools. Experts have projected the number of connected IoT devices to grow to 22 billion by 2025 which is frankly just astonishing to say the least.
Industrial IoT
Industrial IoT is the application of IoT technology in an industrial setting especially with focus instrumentation and control of sensors and services that engage cloud technologies.
Industries have in the past used machine to machine communication to achieve wireless automation and control. With the emergence of cloud and allied technologies like machine learning, industries can now achieve a new automation layer and along with it, new business models and revenue.
Edge Computing
Having introduced some IoT concepts and the flow of it all in terms of devices – data communications – processing and analyzing of the data, I think you are ready for how cloud computing comes into all of this and in particular, an industrial IoT solution.
To begin with, edge computing is a distributed IT architecture in which client data is processed as close to the originating source as possible. By placing computing services and hardware like local storage closer to the data source, you benefit from faster, more reliable services with better user experience.
From a company’s viewpoint, you benefit by being better suited to support latency-sensitive applications, offer better services and identify trends. Industrial IoT edge computing is one way you can use to distribute a common pool of resources across a large number of locations. This will help you to scale centralized infrastructure to meet increasing device and data needs.
Benefits of Industrial IoT Edge Computing
The primary benefit of integrating edge computing into your Industrial IoT system is the ability to bring low latency computing to your industry. The benefits can be further described as follows;
Enhancing IT Security
The sheer growth of the IIoT industry has come with some challenges among them cybersecurity. This comes in with the numerous tiny IIoT network points that are all vulnerable to attacks owing to the lack of inbuilt security features. This creates tons of weak links in the IT ecosystem and is basically an easy game for attackers.
Applying industrial IoT edge computing can prove key in helping you tackle these challenges.
How this works is edge computing can essentially reduce the points of failure, the weak links I mentioned earlier, that can be exploited. Edge computing provides the necessary isolation to make the network more fault-tolerant and resilient.
Revolutionizing Automation
IIoT without a doubt can enable a radical shift in automating industrial processes and operations through the complete integration of edge computing in the devices and processes that drive operations.
Some sticky situations however inadvertently arise where devices produce large data sets. The data has to be relayed to centralized systems for analysis and the devices have to wait for control actions to be generated. This slows down the whole automation process.
Edge computing can be integrated to eliminate communication and processing time lags to enable real-time automation which paves way for autonomous factories in the future perhaps.
Reduced Bandwidth and Latency
In a large industry, it is expected to have massive data volumes and a traffic jam of sorts can be created. Edge computing takes some of the load off of cloud-based platforms in terms of cleaning, structuring and analyzing data.
This in turn helps shave off a load of latency reducing the return time from the cloud back to you. On top of that, you will have more cloud services free for more critical tasks like analytics.
In matters of bandwidth, less data is sent to the cloud with more data being processed, analyzed and stored locally. This leads to less data flow which minimizes the cost with lower bandwidth being used which as a bonus means less frequent upgrades to your cloud storage subscription.
It’s not all good however with edge computing as one of the industrial IoT solutions and here are some of the negative factors it brings along;
Some Disadvantages of Industrial IoT Solutions
Lost Data
After collection, some edge computing devices are programmed to discard irrelevant data. If the latter isn’t the case, relevant data may be lost which messes up the whole analysis process in the cloud.
Cost and Storage
The aspect of cost is associated with replacing or upgrading your existing infrastructure to handle edge computing with tweaks like creating storage capacity for the edge computing devices being required.
