Fog and Edge computing are all the rage among organizations looking for ways to expand the reach and reliability of their networks. The terms are often used interchangeably, which has contributed to the idea that they refer to the same thing. While fog and edge computing share a number of characteristics, they do have some differences that make it worthwhile to think of them separately.
Here are a few things you need to know about these solutions:
Fog computing extends the reach of a cloud network by utilizing localized data centers, or “fog nodes,” to store and process data closer to the source. Under a fog computing architecture, data collected by devices along the edge of the network is transmitted to the local fog node for storage and processing. The fog node then decides what data needs to be relayed back to the network’s central cloud server and what can be processed locally.
Serving as a gatekeeper of sorts for data traffic, fog computing reduces the bandwidth strains on networks by keeping non-critical data on the outskirts. Fog data centers can communicate faster with local devices, analyzing and applying the data they transmit immediately rather than waiting for it to bounce all the way to the central cloud server and back. By discriminating and prioritizing data to determine what needs to go to the cloud, fog nodes help improve overall network performance.
While edge computing can broadly refer to the concept of pushing data storage and processing closer to the data’s point of origin, it’s usually used to describe how devices along the edge of the network handle the data they produce. In a true edge computing architecture, intelligent devices serve as another storage and processing point in the network. Rather than automatically sending data to a local fog node or the central cloud, edge devices have the ability to process data locally, further reducing the bandwidth strain on the network and improving speed.
Advancements in computer processing have made it possible for Internet of Things (IoT) devices to do more than just passively collect data. Edge computing allows companies to get the most out of that processing power and take some of the burden off their data centers or servers. By reducing the physical distance data has to travel before it can be applied, edge computing greatly reduces latency and offers unparalleled flexibility, especially for industries that rely upon real-time data.
In practice, fog and edge computing usually complement one another to the extent that they’re referred to interchangeably. Most well-designed edge computing architecture makes use of fog nodes, creating a complex network that manages data in the most efficient way possible. By integrating the two approaches, organizations can prioritize what data flows through their network and establish clear guidelines to determine where it goes and when.
The distributed nature of fog and edge computing make the architecture extremely flexible. It’s especially useful in areas with low bandwidth connections because it keeps data “close to the ground” or near the point of origin where it won’t bog down the already limited network traffic. Since the network is already so segmented, security features can (and should!) be installed at each point in the network, creating a series of virtual firewalls that can keep data secure and compartmentalized in the event of a network breach.
The rapid development and spread of IoT devices open up exciting possibilities for fog and edge computing. As these devices become more and more versatile, the edge of the network is being pushed farther than anyone considered possible in the past. With smart IoT devices becoming an important part of many companies’ future data strategies, fog and edge computing networks will continue to proliferate. Even for industries that don’t utilize IoT devices extensively, the speed and reliability advantages offered by fog and edge architecture is too important for any company to ignore while anticipating their future data needs.
Manufacturing, utilities, energy, and transportation industries are expected to adopt edge computing strategies first, followed by municipalities, agriculture, healthcare, and retail. In addition to the speed and versatility advantages, fog and edge computing solutions are also easily scalable. Localized fog data centers offer the same wide range of services as a traditional data center and can easily incorporate whatever network solutions a company is looking for. And for companies that rely increasingly on the edge computing capabilities of IoT devices, expanding their network reach is (almost) as simple as producing more devices.
While very similar and often interconnected in practice, fog and edge computing represent distinct solutions to expanding the reach and capabilities of a computing network. As speed and versatility continue to be vital concerns for data management and and processing, companies would do well to explore the full potential of these new approaches to building a network architecture.
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