Fog vs. Edge Computing: The Difference Higher Education IT Teams Should Know

Education Technology Insights | Wednesday, June 05, 2019

FREMONT, CA: With the advancement of technologies across several industries, the idea of the internet of things (IoT) might seem to be yesterday’s concept. Based on recent infrastructural advances in IoT technology, the notion of fog and edge computing is slowly diffusing into IT conversations. The future of higher education is enforced to associate the syllabus with newer concepts to provide with a high-end learning structure. Several campuses have already incorporated cloud computing solutions for controlling and adapting college campuses to fit specific needs. Cloud computing platforms can provide robust data storage and secure medium for systematic university management. 

The fog and edge computing in the educational field is the network and system architecture that attempt to collect, process, and analyze data for providing efficient functioning solutions. Fog computing is an even spread of actions across the network and the central node which stores, computes, and secures information beneath the cloud layer. The decentralization of data across different systems allows information to travel back and forth from various IoT devices uninterruptedly. The information storing nodes and computing nodes are closer to the data source. The closure of data sources with information storing nodes and computing nodes reduces the latency. The fog computing can be a powerful tool for application requiring rapid data transfer speeds such as mixed reality gadgets, artificial intelligence, and 5G network integration. As the application of fog computing includes faster data speed, the higher education IT teams can utilize the upgraded infrastructure for empowering smart campuses, in-ground vehicle detection, and holographic teaching techniques.

On the other hand, edge computing drives the intelligence and communication capabilities toward the edge appliances directly into programmable automation controllers (PACs). The time required by an IoT generated data set to travel back and forth from cloud network to source could be reduced by utilizing edge computing. In 2017, Nokia partnered with the University of Notre Dame to provide a combination of Nokia’s MEC platform and its AirFrame servers as a multi-access edge computing for Compton Ice Arena. The Compton Ice stadium acquired the ability to stream videos on four separate platforms within a 500-millisecond delay.

While the concept of fog computing and edge computing sound quite indistinctive to one another, the main difference is that fog computing always utilizes edge computing but not the other way round.

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