On the edge: how a new approach to data handling can enhance teaching and learning
Why edge computing is a critical element in digital transformation for education and research
As technology continues to transform education and research, the importance of data handling is growing.
The sector generates massive volumes of data every day and, fueled by the move towards blended learning, smart campuses and virtual learning spaces, the demand for real-time processing of that data is only going to increase.
Much of it has a short lifespan: it requires immediate, actionable analysis in order to be useful. Smart buildings management systems, for example, or multi-camera video analytics.
And most data is also subject to strict governance on where it resides: on-premise or in-country, with all the associated security issues that go with transferring it between networks.
Not only that, but real-time applications such as virtual reality and AI are driving demand for minimal latency: milliseconds matter when it comes to making blended learning as seamlessly interactive as possible.
Edge computing presents a new approach to data handling which addresses all these issues.
Bringing data closer to the user
Essentially, it’s about shifting computation closer to the point of data collection and processing rather than relying on a central location.
Instead of pushing vast amounts of data to a public or private cloud for computing and storage, it’s processed locally at the network edge, and only the results are transferred. This eliminates latency issues that might affect application performance, making activities and processes faster, less disjointed and more accessible, adaptable and cost-effective.
Institutions can save money, too. by having processing done locally. Smart campuses with video surveillance, facility management and energy tracking systems, for example, can especially benefit when data processing is carried out on-campus rather than incurring high bandwidth costs transferring it to the public cloud.
The same applies to researchers whose work involves large data sets.
Cloud or edge? Or both?
More applications and services are moving to the cloud, which forms an integral part of any IT organisation’s strategy. However, traditional cloud may not be the answer to all current data computation requirements, especially in the education and research sector.
In public cloud solutions, for instance, network delays between an endpoint and a cloud data centre can adversely impact the kind of real-time applications that are fundamental to education and research. The transfer of enormous data sets in and out of the public cloud may also be cost-prohibitive or violate compliance obligations such as data sovereignty.
To improve performance for specific workloads that require low latency and/or involve large data sets, institutions need to move the power of cloud closer to their network perimeter.
This can be achieved by including edge computing in a digital transformation strategy to complement cloud and data centre infrastructure.
How can edge computing add value to education?
Of course, not everything is suitable for edge computing, but it is a very good fit and highly appropriate for certain environments in tertiary education, such as smart campuses, virtual learning spaces and large research projects.
Edge is right for any workload that needs to reach geographically distributed end users quickly, reliably and without interruption. It’s good for real-time local tasks that need a fast response, and it can also be useful where connectivity is weak or bandwidth is restricted.
Edge computing can improve the student experience
Edge computing improves learning outcomes by addressing vital infrastructure challenges such as bandwidth limitations, excess latency and network congestion which can hamper access to blended learning.
It enables seamless interactions in physical, virtual or immersive learning spaces, and institutions can use its ability to process data in near real time to build more personalised interactive experiences such as extended reality and advanced chatbots.
And, because edge computing data is stored locally not centrally, a single cyber-security disruption will not necessarily affect the entire system. In other words, edge comes with a layer of cyber protection.
Where to start?
At Jisc, we are seeing growing demand for cloud resources to be made available closer to users.
One of the ways we’re making edge computing available to members is via our smart campus project with Honeywell. This aims to establish a common core platform running on the Janet Network that will enable the sector to collect, process and utilise data from on-site smart devices and sensors connected to the internet of things (IoT) to make campus buildings healthier places to be.
In a first for the sector, we are also working with companies like AWS and Fortinet to create and test a secure, high-performance hybrid cloud environment which the UK education and research sector can share.
This proof-of-concept solution brings the power of AWS into the core of Janet, at the edge of organisations’ networks, creating an environment which enables anything that can be done in the cloud to instead be done at the edge. Based on AWS Outposts, this will effectively enable institutions to access additional compute power via Janet instead of building their own edge computing infrastructures or using the public cloud.
To find out more about edge computing and how Jisc is working to make this capability available to the sector, book to attend Networkshop 2023.
To see how Jisc can support the move towards smarter campuses and healthier buildings, book a demo of the Honeywell Forge platform with firstname.lastname@example.org
For more information on AWS Outposts, contact email@example.com
Alternatively, members should contact their Jisc relationship manager.