Close to the edge

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Edge computing’s processing model makes it extremely well suited to IoT as it can cope with the tsunami of data that ‘things’ will generate.

IDC estimates that by 2019, 45% of IoT-created data will be stored, analyzed and acted upon close to or at the edge of the network. It is little wonder that cloud vendors such as Microsoft and Amazon are already promoting the concept of edge. With Azure IoT, for example, Microsoft is making it easier for developers to move some of their computing needs closer to the edge, enabling them to run cloud intelligence locally instead of having to hop backwards and forwards to the cloud.  At the same time, Amazon Web Services (AWS) is touting Greengrass to enable edge devices to process data and communicate with the AWS cloud.

Gaining an edge

Edge computing brings a broad array of benefits to the world of IoT. Firstly, advanced on-device processing and analytics has a big impact on latency. Why? Because it dramatically cuts down on the amount of data being moved together with the distance it needs to travel, providing actionable insights faster. This is paramount for critical applications in finance, manufacturing or on-board automobile safety, for example.

Key to edge computing’s appeal is its ability to offer real-time or near real-time data analysis capabilities. This allows data to be examined at the local device level, as opposed to a distant cloud or data center, which can cut analysis time from minutes to seconds for remote cases such as wind turbines, for example. Analysis at the edge also lowers costs related to data management and ensures that if one device becomes faulty the rest of the assets remain operational.

Edge can also help to reduce connectivity costs by sending on only principal data to the cloud for processing, instead of a deluge of raw data. This is a boon to ‘things’ that connect to LTE networks, such as smart meters. It also allows for offline validation of data which reduces the amount of end-to-end bandwidth required.

Significantly, edge addresses security and compliance issues that have been a barrier to some organizations adopting cloud.  With edge, organizations can sieve out sensitive, personally identifiable data locally, sending only the non-sensitive information to the cloud or data center for processing. This is relevant where targeted marketing campaigns are being run, for example. It can also buoy up cyber defences such as allowing for deployment of encryption in the local area network before the data travels to exposed parts of the internet.

Finally, edge can help in protecting current investment in IT by converting communications protocols on legacy devices to ones that smart devices and the cloud can read, opening up the connection of legacy devices to IoT platforms.

Relationship with Fog computing

Edge and fog computing are often referred to in the same sentence, but they are two very different beasts. Both have the ability to process data closer to the user to reduce latency and filter data. But it is the actual location of the devices that separates them.

Fog computing drives data validation and processing intelligence into the local area network, processing the data in a so called fog node or IoT gateway. Edge computing, however, pushes it directly onto central edge devices such as switches or routers or licensed spectrum wireless networks.

The Open Fog Consortium describes fog computing as “the missing link in what data needs to be pushed to the cloud and what needs to be analyzed locally – at the edge”. It views edge and fog computing as ‘synergistic’, describing “edge is to fog as apple is to fruit”.

One thing is for sure, both add a layer of complexity to compute, storage and network architectures, which despite their innate advantages can increase costs if not carefully designed and deployed.

Edge – the next frontier

Enterprises are fast seeing edge computing as a practical way to analyze and store data, offering location optimization, security and all important speed when it comes to data crunching.

The arrival of virtual reality and artificial intelligence applications, which will demand gargantuan amounts of data be processed in real-time at low latency will accelerate the take up of edge computing.

Don’t read this as the death knell for cloud, however. With more ‘things’ generating increasing amounts of data, it makes common sense to advance cloud capacity to the edge. Cloud will still have an important role to play, but it is no-longer a single, straight highway.

In a rapidly changing digital world, the Internet of Things and data analytics are reshaping the way companies do business, whatever their size or activity. Find out more here

Jan Howells

Jan has been writing about technology for over 22 years for magazines and web sites including ComputerActive, IQ magazine and Signum. She has been a business correspondent on ComputerWorld in Sydney and covered the channel for Ziff-Davis in New York.