Edge computing: What you need to know
8 July 2021 | 0
In association with RS Ireland
With the increasing adoption of the Industrial Internet of Things (IIoT) principle – the idea that releasing more data from industrial processes and machines allows businesses to make faster, more informed, better quality decisions – technologies have emerged that support IIoT in realising its full potential.
Edge computing is one such concept, but what is the ‘edge’? In most cases it is the point of the local network on which IIoT connected devices communicate. In industrial terms this is most likely an Ethernet network – either specific to a single machine, process or a local site network.
While data can flow within this – often closed – network it may not be suitable for pushing to the cloud, or only certain elements of the data are desirable for remote analysis. Edge computing primarily focuses on the task of data collection, interrogation and manipulation on the network edge, forming a link to cloud services or the wider Internet.
What is an edge controller?
First a little bit of terminology. IT is the infrastructure and networks for all the computing, data storage and Internet connectivity used within a traditional business. OT – operational technology – is all the industrial control systems, field buses and device specific protocols which industrial process control use.
This is where an edge controller comes in. It acts as the bridge between fieldbus data from sensors or trapped within closed PLC networks (OT) by capturing it, and then processing and packaged the data for use within cloud-based dashboards (IT) or condition monitoring services.
The real power of any edge controller is its potential to unlock data which was previously inaccessible. This data, more often than not, can provide operations and engineering teams with insight that can help them identify efficiencies or spot performance changes that indicate early signs of failure, enriching their decision-making process.
Challenges to overcome
Though the advantages that edge computing presents are clear. It is not without its drawbacks. The costs of having processing and data storage functions at many different locations raise the capital expenditure involved. There will likewise be increased operational costs to factor in, due to the need to maintain the expansive processing/storage assets comprised. Concerns about operational reliability must also be considered. To address this, it is important that adequate redundancy is designed into the distributed topology to prevent any point of failure leading to unwanted disruption.
Data storage being distributed throughout the network, either at cloudlets or at the actual nodes, greatly increases the attack surface for hackers to try to exploit – heightening the risk of a potential security breach occurring. That said, by not having data all located in one centralised place, the possibility of a large-scale attack is averted.
Though certain aspects of edge computing are not ideal, they must be balanced against the unquestionable appeal that improved latency and reduced network traffic brings. These are things that are not just desirable, but completely essential to a multitude of nascent applications that will come to the fore in the years ahead. There is no doubt that edge computing is destined to become a part of our evolving digital landscape. It will work in tandem with existing cloud-based topologies, with each of these being optimised for different use case scenarios.