Edge Computing: What It is and How It’s a Game-Changer
If cloud computing has been at the top of CIO’s minds for the last dozen years, Edge Computing is now taking its place. For those not yet familiar with the term, edge computing processes data at the edge of the network, as close to the point of its creation as possible. Take for example autonomous cars, they are full of embedded technologies, sensors and communication systems continuously generating data. If they have to send the data that they collect through systems like GPS, Lidar (a surveying method that measures distance to a target by illuminating that target with a pulsed laser light) and video cameras (they keep track of the positions of other vehicles, look out for pedestrians and obstacles) to the cloud for processing and then wait for analysis and insight before action is taken…well, accidents can happen. Much of the data that is collected at the edge of the network needs to be processed in real time by edge computing so analytics can be done and knowledge can be transferred in places where split seconds matter.
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Like a Data Center on Wheels
Peter Levine, a general partner at the venture capital firm Andreessen Horowitz who was previously senior vice president and general manager of the Data Center and Cloud Division at Citrix, has called autonomous cars “data centers on wheels” and drones “data centers with wings.” While a year ago he may have seemed “out there,” to many IT managers, today he makes perfect sense. In fact, Hadoop distribution providers like MapR, who have spent the last few years readying their wares for the Cloud, also offer products for the edge. And it is not only automobiles that need to be able to process data at the edge to function properly, there are also Internet of Things (IoT) devices like oil rigs out in the field where Internet connectivity may be limited or sporadic, making communication to the cloud unreliable.
Constellation Research vice president and principal analyst Holger Mueller offers another example of edge computing, “When local software shuts down a windmill because it risks breaking due to excessive wind speeds, that is edge computing. Edge is often motivated by moving the code to the data because transferring the data is too slow or too expensive.”
Recent Gartner research, entitled, Cool Vendors in IoT and Edge Computing,2017 (Fee Charged), echoed Mueller’s conclusion, “As market adoption of IoT grows, IoT endpoints generate ever-higher volumes of data. As a result, streaming all of the information to the data center or the cloud for management, analysis and decision making can be costly and inefficient.”
But that is not the only reason edge computing has become a game-changer. The Gartner analysts wrote that certain modern applications such as those from autonomous machines running AI models locally demand “architectural elements different than that which cloud and data centers can offer. Traditional data centers or centralized cloud architectures are not aligned with these emerging requirements.”
It’s worth noting too that the widespread acceptance of microservices has helped companies embrace edge computing because they enable faster data interpretation and usage.
What is Fog Computing?
Fog computing according to The US office of National Institute of Standards and Technology (NIST) is “a horizontal, physical or virtual resource paradigm that resides between smart end-devices and traditional cloud or data centers. This paradigm supports vertically-isolated, latency-sensitive applications by providing ubiquitous, scalable, layered, federated, and distributed computing, storage, and network connectivity.” While some say that fog computing not only encompasses edge computing but also includes the network required to get processed data to its final destination, others believe that the founders of the OpenFog Consortium, Cisco, Intel, Microsoft, and Dell EMC created it as a “commercial way to use distributed resources as one system, so it’s a reason / excuse / sales argument to buy more on premises gear, as you can all use it together,” says Mueller.
Gartner has said that Fog Computing is a new model aimed at assuaging security and analytics concerns because it may provide a greater degree of system intelligence enabled at the edge. In other words, when it comes to Fog Computing, the jury is still out. Edge computing providers and users can see if they can provide the needed security on their own or if going the way of the Consortium is their best bet.
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Edge Computing Security
Because edge computing leverages data from IoT connected devices, many of which were designed with an open protocol and “implicit trust,” security is of concern.
“Vulnerabilities in Internet of Things (IoT) devices will create mass confusion, leading to new security regulations. In 2018, we’ll see cyber criminals take this to the next level by hacking the IoT to create real-world mayhem. The interconnectedness of IoT devices make them prime targets for advanced hacks and ransomware. Imagine what people would pay if their smart thermostat or their connected vehicle were taken over?” asked Experian in its 2018 Data Breach Industry Forecast.
Proponents of edge computing claim that computing at the edge is safer because data is not traveling over a network; however, opponents claim that edge computing is less secure because the IoT devices are more susceptible to begin with. Vendors that provide products and services at the edge say they are tackling the problem.
Microsoft for example, claims that edge computing solves a security problem. “Edge computing helps to address the security and compliance requirements that have prevented some industries from using the cloud. With edge computing, companies can filter out sensitive personally identifiable information and process it locally, sending the non-sensitive information to the cloud for further processing.”
At the end of the day, there is still work to be done and researchers are digging into the technology in subject areas like reconfigurable security.