Just as fog is a cloud that hugs the Earth, fog computing brings the cloud\u2019s power \u2013 such as storage, networking and data management \u2013 to the data\u2019s source.<\/p>\n<\/blockquote>\n
According to the Journal of System Architecture, fog computing means computation, decision making and data management happen on the path between internet of things (IoT) devices and the cloud<\/a>. It links to edge computing<\/a>, where data is processed close to its source to avoid processing in the cloud. Fog computing defines how edge computing works, and facilitates services between end devices and cloud data centers. Cisco defines<\/a> the difference: edge is the concept; fog is the standard that delivers scalable performance.<\/p>\n
With fog, security must be provided at the edge or in dedicated fog nodes, as opposed to central security mechanisms for cloud data centers.<\/p>\n
Industry needs to beat the cloud lag<\/h2>\n
Why is fog a step up from using cloud alone? Well, cloud is great<\/a> if you don\u2019t need to send data to and from the data center instantly.<\/p>\n
You won\u2019t notice the cloud lag if you\u2019re preparing a sales report. But in industrial automation, a second\u2019s delay, or even a microsecond, can spell disaster.<\/p>\n<\/blockquote>\n
These legacy systems prioritize safety but weren\u2019t all designed to connect to the internet. Today, even firm believers in the air gap approach<\/a> (when to avoid cybersecurity risks, you prevent a computer storing valuable information or controlling a critical process ever connecting to the internet) are tempted to use machine-learning algorithms. Meanwhile, most also know the benefits of using data to optimize industrial processes.<\/p>\n
Data collection can be a jumbo problem<\/h2>\n
Engineering company Rolls-Royce reaps the benefits of machine learning on sensor data collected in the cloud. Not from their legendary cars, but their aircraft engines. 4,500 turbines continuously send real-time data about consumption, pressure and temperature to Rolls-Royce\u2019s data centers<\/a>. Machine learning predicts and plans maintenance routines, sending parts and personnel to a specific airport before the plane lands. It optimizes logistics, reducing delays and overheads. But these benefits come at a price: One Boeing 787 flight with two Rolls-Royce engines generates 500 GB of data. For long-distance, it may be terabytes.<\/p>\n
How could you streamline this? You could collect only some of the sensor data. But how do you decide what to drop, so you don\u2019t lose something essential for safe operations? Fog computing may be the answer.
\n
\nIn 2016 Cisco and machine tool builders Yamazaki Mazak began a pilot to demonstrate the benefits of fog computing for industrial automation<\/a>. (Yamazaki Mazak sponsors the McLaren team in Formula 1 racing, rivals of my favorite Scuderia Ferrari<\/a>.) The pilot processes industrial internet of things<\/a> (IIoT) data from sensors in machinery, detecting sudden temperature spikes, changes in pressure and coolant liquid levels. Like Rolls-Royce, they want to improve safety and predict maintenance cycles. The benefit is broadly the same, but with less data sent to the cloud.<\/p>\nA bright future in the fog<\/h2>\n
Fog computing hasn\u2019t had the same recognition as the cloud, but I think that will change. We\u2019ve seen exponential growth in sales and the computing power of IoT and IIoT devices. The importance of this data to business will keep growing. My colleagues at Kaspersky will stay busy enhancing our cloud security solutions, as seen with our hybrid cloud team adding protection against supply chain attacks<\/a>.<\/p>\n
Whether you\u2019re flying high in the cloud or keeping data close to its source with fog computing, protecting your industrial technology with up-to-date and effective enterprise-grade cybersecurity will be critical to surviving and flourishing in the future.<\/p>\n","protected":false},"excerpt":{"rendered":"
When cloud computing doesn\u2019t have the speed real-time industrial internet of things (IIOT) data demands, fog computing is a shining light.<\/p>\n","protected":false},"author":2540,"featured_media":36297,"template":"","coauthors":[3595],"class_list":{"0":"post-36296","1":"emagazine","2":"type-emagazine","3":"status-publish","4":"has-post-thumbnail","6":"emagazine-category-cloud","7":"emagazine-category-industrial-cybersecurity","8":"emagazine-category-internet-of-things","9":"emagazine-tag-cloud-computing","10":"emagazine-tag-data-security","11":"emagazine-tag-industrial"},"hreflang":[{"hreflang":"x-default","url":"https:\/\/www.kaspersky.com\/blog\/secure-futures-magazine\/fog-computing-2\/36296\/"}],"acf":[],"_links":{"self":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/emagazine\/36296","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/emagazine"}],"about":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/types\/emagazine"}],"author":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/users\/2540"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/media\/36297"}],"wp:attachment":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/media?parent=36296"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/coauthors?post=36296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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