IDG Contributor Network: Challenges in realizing the promises of the holistic edge

Cloud providers such as Amazon, Google, Facebook and Microsoft are already rolling out distributed cloud infrastructure. Whilst the central cloud is established as an integral part of current and future networks, there are key issues that make the central cloud simply not the solution to several use cases.

  • Latency, also known as the Laws of Physics: The longer the distance is between two communicating entities, the longer the time it takes to move content there. Whilst the delay of reaching out to the cloud today might be tolerable for some applications, it will not be the case for emerging applications that will require nearly instantaneous responses (e.g. in industrial IoT control, robots, machines, autonomous cars, drones, etc.).
  • Data volume: The capacity of communication networks will simply not scale with the insane amount of raw data that is anticipated will need ferrying to and from a remote cloud center.
  • Running costs: The cost of a truly massive computational and storage load in the cloud will simply not be economically sustainable over the longer term.
  • Regulatory: There are and will very likely be new constraints (privacy, security, sovereignty, etc.) which will impose restrictions on what data may or may not be transferred and processed in the cloud.

So it certainly does make sense to distribute the cloud and interconnect this distributed infrastructure together with the central cloud. This process has already begun. One good tangible example is Amazon’s launch of the AWS GreenGrass (AWS for the Edge) product and their declared intentions to use their Whole Foods Stores (in addition to the small matter of selling groceries) as locations for future edge clouds/data centers. In general, cloud providers, perhaps driven by their real estate choices, have a relatively conservative view of the edge, restricting it to a point of presence typically 10 to 50 km from the consumer.

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Computerworld Cloud Computing

Edge computing: What you need to know before you deploy

I explained edge computing back in May, and how it’s related to cloud computing. But I continue to get questions on the use of edge computing, especially on whether should enterprises begin to use edge computing anytime soon. 

To make that decision, there are three aspects of edge computing that you should consider:

1. Edge computing is tactical, not strategic

Edge computing is about putting processing and data near the end points. This saves the information from being transmitted from the point of consumption, such as a robot on a factory floor, back to centralized computing platforms, such as a public cloud.

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InfoWorld Cloud Computing

Edge computing will blow away the cloud

SAN FRANCISCO — The ubiquitous cloud computing craze may not be long for this world if venture capitalist Peter Levine is right. The Andreessen Horowitz general partner said that as more computing capabilities move to so-called “edge” devices, including anything from driverless cars and drones to the boundless devices that make up the internet of things (IoT), the cloud will slowly evaporate.

“A large portion of computation that gets done in the cloud today will return to the edge,” said Levine at the Wall Street Journal’s CIO Network event here Tuesday.

Levine said the driverless car, whose 200-plus CPUs effectively make it a “data center on wheels,” is a prime example of an edge device whose computing capabilities must be self-contained. Levine said that an autonomous vehicle relying on the cloud fo

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Network World Cloud Computing

IDG Contributor Network: Qwilt moves content delivery to the edge

The other day I was quietly driving along a country road near where I live and happened across an irate looking driver, parked up at the edge of the road. Much of his irate-ness was, I assume, caused by the fact that he was driving a late model, European sports car which had unceremoniously broken down rendering him hot (it’s summer in the Southern Hemisphere), immobile and in possession of a very expensive hunk of steel and alloy.

As I left the scene, with him not wanting outside help, I got thinking about how being broken down on the side of a road with a very expensive vehicle is analogous to having some fantastic content on the internet that, alas, can’t get to those who want to view it. It looks good, but is pretty much useless to everyone.

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Computerworld Cloud Computing

IBM and Cisco are taking IoT analytics to the edge

The Internet of things is no good without a way to act on the data it generates. A new partnership between two of the biggest IoT players promises to put smart collection and advanced analysis of data right where it’s needed.

IBM and Cisco Systems have worked out how to run components of IBM’s Watson IoT analytics on Cisco edge devices. This will bring more intelligence closer to where the action is, helping enterprises run things like factories and oil rigs more efficiently.

In 2014, Cisco unveiled small routers and switches that could be embedded in facilities and vehicles located far from any data center. The devices could take in data from local sensors and analyze it on site with a small, built-in Linux computer. Among other things, this “fog computing” system could decide what data was interesting enough to send to the cloud and what could just be thrown away.

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InfoWorld Cloud Computing

IBM and Cisco are taking IoT analytics to the edge

The Internet of Things is no good without a way to act on the data it generates. A new partnership between two of the biggest IoT players promises to put smart collection and advanced analysis of data right where it’s needed.

IBM and Cisco Systems have worked out how to run components of IBM’s Watson IoT analytics on Cisco edge devices. This will bring more intelligence closer to where the action is, helping enterprises run things like factories and oil rigs more efficiently.

In 2014, Cisco unveiled small routers and switches that could be embedded in facilities and vehicles located far from any data center. The devices could take in data from local sensors and analyze it on site with a small, built-in Linux computer. Among other things, this “fog computing” system could decide what data was interesting enough to send to the cloud and what could just be thrown away.

To read this article in full or to leave a comment, please click here

Computerworld Cloud Computing