Each new technology comes to replace the old one. Sometimes, as in the case of cloud technologies, re-branding old ones is done to make them more attractive to consumers and, thereby, create the illusion of a new product. Cloud computing previously existed in one form or another. At one stage they were called “on demand computing”, and then they were transformed into an “application service provider” (ASP).
Now there is edge computing, to which industry observers and experts predict the ability to replace the cloud. But the question is: will this really happen?
About Edge Computing Briefly
First, let’s figure out what, exactly, edge computing is? The most important difference between edge computing and cloud computing is that data collection and analysis is not done in a centralized computing environment, such as a data center, but in the place where data flows are generated. Data sources are digital devices (not necessarily located in one location), which then transmit this data in real time (depending on the situation, the transfer of information may be delayed) to the central repository.
What is their significance? Experts predict that by 2020 there will be more than 5 million “smart” sensors and other IoT devices in the world that will generate at least 507.5 zettabytes of data. Edge computing will help companies to digest this mountain of information.
What does their influence extend? IOT and boundary computing will be used in many industries, including hospitals, retail chains and logistics service providers. The directors of enterprises, business leaders and production managers are the circle of stakeholders who will decide on the implementation of edge computing.
So why do people think that edge computing will defeat the cloud? This claim was stated in many articles. For example, Clint Boulton writes about this in the article “Edge Computing Will Blow Away the Cloud”. He refers to the venture capitalist Peter Levine, a general partner at Andreessen Horowitz, who believes that more computing resources will move towards finite devices – such as driverless vehicles and drones – that make up at least part of the Internet of things. Levine predicts that this will mean that the cloud has come to an end. The data processing process will move back towards the edge computing.
In other words, now there is a tendency to centralize computing in data centers, while previously it was often decentralized or localized nearer to the point of use. Levine sees an driverless vehicle as a data center: they have more than 200 processors capable of providing complete fault-tolerance to avoid an accident on the road. The nature of autonomous vehicles means that their computing power must be independent and in order to ensure security it is necessary to minimize any connection that they have with the cloud. Nevertheless, they can not do without it completely.
These two approaches can complement each other. Some of the arguments for edge computing simply disappear when it comes to increasing the amount of data that leads to an even more frustrating and slow network. Delay is the culprit. The data becomes more and more: the amount of data per transaction, the “heavy” video and a lot of data from different sensors increase. Virtual and augmented reality will play an increasingly important role in its growth. With such an increase in the amount of data, it is more difficult to solve the delay problem than it was before. Now it makes sense to place data closer to devices such as an driverless vehicle to eliminate the delay, but nevertheless most of the data is still remotely located in the cloud. The cloud will continue to be used as a provider of services, such as media and entertainment. It can also be used for data backup and for data exchange originating from a vehicle.
Let’s digress a little from autonomous vehicles and return to a more familiar business. The creation of a number of small data centers or disaster recovery sites can reduce the scale effect, as a result, increase costs and make work less efficient. Yes, the delay can be reduced, but in case of catastrophe the consequences will be no less deplorable; so to ensure business continuity, some data should be stored and processed elsewhere – for example, in the cloud. In the case of driverless vehicles, since they must operate regardless of whether there is a network connection or not, it makes sense that certain types of computation and analysis are performed by the vehicle itself. However, this data will still be backed up to the cloud when the connection is available. The approach will be hybrid: edge and cloud computing will complement each other, and not be used alone.
From the Periphery to the Cloud
Saju Skaria, a St. Director at TCS, offers several examples where edge computing can be useful. In his article “Edge computing vs. Cloud computing: where does the future lie?” (https://www.linkedin.com/pulse/edge-computing-vs-cloud-where-does-future-lie-saju-skaria) he writes the following:
Edge computing does not replace cloud computing, however. In reality, an analytic model or rules might be created in a cloud then pushed out to edge devices. Some edge devices are also incapable of doing analysis.
He then goes on to talk about fog computing, which includes processing data from the periphery to the cloud. He believes that people should not forget about data stores, because they are used for “slow analytical queries and massive data storage”.
Edge Beats the Cloud
Despite this argument, the Gartner’s analyst Thomas J. Bittman believes that “Edge Will Eat the Cloud”: “Today, cloud computing is eating enterprise data centers, as more and more workloads are born in the cloud, and some are transforming and moving to the cloud….But there’s another trend that will shift workloads, data, processing and business value significantly away from the cloud. The edge will eat the cloud…and this is perhaps as important as the cloud computing trend ever was”. (https://blogs.gartner.com/thomas_bittman/2017/03/06/the-edge-will-eat-the-cloud/).
Later in his blog Bittman writes: “The agility of cloud computing is great—but it simply isn’t enough. Massive centralization, economies of scale, self-service and full automation get us most of the way there — but it doesn’t overcome physics — the weight of data, the speed of light. As people need to interact with their digitally-assisted realities in real-time, waiting on a data center miles (or many miles) away isn’t going to work. Latency matters. I’m here right now and I’m gone in seconds. Put up the right advertising before I look away, point out the store that I’ve been looking for as I drive, let me know that a colleague is heading my way, help my self-driving car to avoid other cars through a busy intersection. And do it now”.
Bittman makes some just observations, but he uses an argument that is often used for delays and data centers: they must be located close to each other. The truth is that global networks will always be the foundation of edge computing and cloud computing. Secondly, Bittman did not come across any data acceleration tools, such as PORTrockIT and WANrockIT. While physics is certainly a limiting and complex factor that will always exist in networks of all kinds – including WANs, today you can place your data centers at a distance from each other. The delay can be reduced and its impact can be leveled, regardless of where the data is processed, and regardless of where the data is stored.
How Quickly Will the Technology Implement?
Can we say that edge computing has penetrated the commercial sector of the economy? A study conducted by Tech Pro Research in 2016 showed that more than half of the respondents started implementing IoT in combination with edge computing technology. Among them were SMB companies and large enterprises. Some vendors noted that they are engaged in the implementation of edge computing, guided by their own IoT-strategies. In any case, even if one or another vendor is not aimed at immediate implementation, its road map still needs to have hints or even a developed strategy for deploying edge computing.
If these conditions are met, it will reach the second stage – to find an IT service provider that offers services for the deployment of the IoT infrastructure. For this provider – especially for large ones – the provision of basic services, including storage services, server capacity, virtual networks, access channels and IoT devices. The availability of cloud services allows enterprises of all sizes to shift their computer facilities and data stores closer to the edge. It should be borne in mind that cloud vendors have the necessary expertise to deploy IoT-services – it remains only to select the necessary ones.
How to Start Implementing of Edge Computing Right Now?
There are two ways to implement the concept of boundary computing in an enterprise: the installation of physical equipment, including servers and data collection devices, as well as cloud solutions. Both are offered by such suppliers as Intel, IBM, Nokia, Motorola, General Electric, Cisco or Microsoft. In addition, there are suppliers on the market specializing in the supply of vertical solutions and IT applications for the protection of the boundary network, monitoring, logistics and production automation. IT suppliers in addition to equipment, software and networks provide consulting services for their configuration and proper implementation.
Thus, edge computing is not a new breakthrough solution. This is just one solution, like the cloud. Together, these two technologies can support each other. The difference between edge computing and cloud computing is that “edge is a method of speeding up and improving cloud computing performance for mobile users”. Thus, the statement that edge computing will replace cloud computing is questionable. According to marketing conclusions, cloud computing can be renamed, but the essence will remain the same.