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What Is Fog Computing? And Why It Matters In Our IoT And Big Data World

Vincent Stokes / 3 min read.
January 3, 2017
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Fog computing is a disruptive technology that adds another level of complexity to Cloud computing, which is the centralization of information into the hands of developers like Amazon (S3) who offer both massive storage and data analytics and processing for the data on their servers. Fog computing is a term that was laid out by a Cisco Systems paper, and is also known by IBM as Edge Computing. Fog computing is positioned to revolutionize production systems, transportation, and even the networks on which we execute business daily.

Contributions to Cloud Computing

Fog computing contributes to the Cloud computing platform by allowing for devices to transmit and process sensory data, system updates, and even application processing amongst themselves. The need for the Fog contribution is shown in a study by Forbes, which points out that the U.S. is ranked 35th for bandwidth per user in the world. This limitation will likely have a lessened impact on business as the Internet of Things and Big Data adapt to Fog Computing and transcend their current bandwidth limits.

Relation to Internet of Things

The discrepancy drives a need for innovation, and the Internet of Things (IoT) allows for devices to share processing power, as well as to push information to other local devices. This capacity to share information between local devices also allows for network and bandwidth loads to see a significant decrease, as the devices in the Internet of things are capable of establishing a network between themselves, which in turn allows for the main connections to be utilized for other tasks. The difference can be equivalent to pushing an update to one device in a city, and that device replicates the update to all of the other identical devices across the city, which allows for a significant decrease in bandwidth usage for mandatory tasks. Application processing speed is one of the key factors in the expansion of Fog computing into the personal use realm, as it allows gaming and other, latency intensive applications to perform at the levels needed for high customer satisfaction.


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How it contributes to Big Data

Fog computing offers significant advances in terms of processing for the Big Data scene, where information is so abundant, that it cannot all hope to be processed. In fact, the biggest issue with Big Data is that all of the industries relying on it must analyze the information for their decision-making process, the volume of data involved means that companies must choose which data sets they analyze. The solution is given a form of solution when Hadoop OLAP (Online Analytical Processing, performed in a Hadoop environment) meets the collective processing power of the Internet of Things. A new level of capability is formed by the efficiency and raw power, as well as the lessened network load, which comes from the very nature of the Internet of Things. This combination allows industries which rely on Big Data and Business Insight to expand their reach in terms of analysis, and therefore capture a wider scope of their customer’s preferences and tendencies. As a result, Fog computing will not be only a disruptive technology but also an important part of the predictive technology realm.

As stated previously, the premise of Fog computing is well on its way to fulfilling its role as a disruptive technology, in that it will allow for industries to experience significantly higher efficiency, as well as even lower costs of operation, compared to a hybridized cloud environment, and even more so over a traditional, in-house computing system. The lower cost, combined with the efficiency model of Fog and Cloud computing allow for even greater strides in industry, civilian safety, and even business transaction speed.

Categories: Cloud, Internet Of Things
Tags: Big Data, Cloud, fog computing, Hadoop

About Vincent Stokes

Vincent Stokes is a freelance writer for Datafloq.

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