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CHIPS Articles: What Is Fog Computing?

What Is Fog Computing?
A newly release NIST publication describes the complex model that supports IoT devices
By CHIPS Magazine - March 19, 2018
Managing and making sense of the enormous volume of data generated by internet of things sensors and actuators is one of the biggest challenges faced when deploying an IoT system. Traditional cloud-based IoT systems are challenged by the large scale, dissimilar elements, and high latency inherent in some cloud ecosystems.

One solution is to decentralize applications, management, and data analytics into the network itself using a distributed and federated compute model, according to the National Institute of Standards and Technology. This approach has become known as fog computing.

In defining this alternative, NIST is releasing Special Publication 500-325, Fog Computing Conceptual Model, which presents the conceptual models of fog and mist computing and how they relate to cloud-based computing models for IoT technologies.

Until recently, much of the data from IoT devices has been managed and stored through cloud computing, a centralized network of computers and servers connected together over the internet. But access to data through the cloud can be sluggish because data needs to be transported to the cloud for processing, analysis and storage, NIST said in a release.

The alternative to cloud computing that NIST describes is fog computing, a decentralized infrastructure in which data is accessed locally, which dramatically reduces the amount of time it takes to access data. The publication presents the conceptual model of fog computing and an alternative model called mist computing and how they relate to cloud-based computing models for IoT. The new document also characterizes important properties and aspects of fog computing, including service models and deployment strategies, and provides a baseline of what fog computing is and how it may be used.

Download SP 500-325 (DOI)

Related NIST Publications: SP 800-145

Authors: Michaela Iorga (NIST), Nedim Goren (NIST), Larry Feldman (G2), Robert Barton (Cisco), Michael Martin (IBM Canada), Charif Mahmoudi (NIST)

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