Fog computing: The alternative to edge computing

Fog computing: The alternative to edge computing

Which of these two technologies is suitable for you? We evaluate them for you.

The advent of Industrial Internet of Things (IIoT) and applications like smart grids and vehicle-to-vehicle communications necessitates faster processing of data, in many cases from sensors deployed at various points. In such scenarios sending the data to the cloud for processing and analysing might result in latency and added costs. To overcome these issues enterprises are considering technologies that help them move data processing and analysis closer to the source of data.

Edge versus fog: What works for you?
While edge computing is one such technology, fog computing is a somewhat similar approach that helps one analyse and transmit data faster. What is common between the two approaches is that both push processing and analytical capabilities closer to the data source, which could include all sorts of devices, including sensors, consumer electronic equipment and various other devices that are IoT enabled. The main difference between the two technologies lies in where the intelligence, processing power and data transmission capabilities are placed. Edge computing pushes these capabilities into an edge appliance directly into devices like Programmable Automation Controllers (PAC).

In a typical fog computing environment these capabilities reside at the LAN. Here the data transmission is done from endpoints to a gateway. From there it is transmitted to sources for processing, analysis and return transmission. Both edge computing and fog computing complement the cloud. While these approaches enable faster short-term processing and analytics, cloud supports longer-term, intensive analytics. Both edge and fog computing help enterprises overcome compliance and security issues involved in sending raw data to the cloud that might reside far away from the source.

Fog computing: Pros and cons
Advocates of fog computing say that it is a lot more scalable than edge computing and, unlike the latter, allows visibility across multiple machines and processes. Other advantages include optimisation of network bandwidth, minimal network latency and reduction in the quantity of data transmitted to the cloud. While fog computing does improve security by keeping data close to the edge, it has some loopholes that could lead to IP address spoofing and issues related to authentication. Privacy could also be an issue. Fog computing as a concept is newer than edge computing. The costs of hardware and various components required to deploy the technology may be on the higher side.

The term fog computing was created by Cisco, and since then many leading companies, academics, and research organisations have joined hands to build an open architecture that will support fog computing. There are also a number of innovative startups working to improve the technology to address IoT applications more effectively.

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