Putting Data to Work, At the Edge

A single word to define the modern era would probably be ‘connected’. Information and Communications Technology (ICT) has evolved a lot in the last century. But the more significant changes have occurred in the past few decades. With transformational technologies like the global Internet, the?public?cloud, and now?edge?computing - the creation, distribution, and processing of information has become more simple and accessible. More data is created and processed today than ever before. And these volumes of data are only set to grow. While this does seem like a good thing, it does bring a few challenges along with it.?

In the past, the primary data challenge for enterprises was about availability. Homegrown data centres were incapable of servicing remote branch offices. It meant the creation of more data centres at remote locations. But then the data and applications were left in silos. The Internet indeed does a fair job in bridging the gap between these geographically distributed systems, but that also posed the challenge of data inconsistency and?a?dependence on high bandwidth capacity. Cloud?computing solves this classic challenge by centralising data and empowering remote compute and storage resources, with shared data centres strategically located across the globe. With data centralised, geographical locations made little difference on productivity and data?consistency.?However,?where?cloud?computing fails is in its inability to provide a viable solution to bandwidth issues and the lack of reliability for time-sensitive data processing and decision making. For example, an autonomous car needs to make quick decisions to avert traffic accidents. Edge computing has emerged to resolve these very issues.?

Why Edge Computing??

Edge computing stems from the need to enhance the application experience at the edge. By edge, we mean distributed geographical locations. The idea behind edge computing is to provide a consistent experience wherever you are. The reasons for inconsistent data delivery and processing are network congestion, bandwidth limitations, and data volumes. If your data always has to move back and forth between your device and the data centre, there will always be a delay (at least slightly), which can make a difference in time-sensitive operations. This delay is called latency. Though cloud computing is a great way to centralise data and attain data consistency, it suffers from high latency issues. Simultaneously, data transfer incurs bandwidth costs which increase with the number of edge devices on your network.?

The simplest definition for?edge computing is to process data at the location where it is generated and resides. Your biometric data on your mobile devices is an example of edge computing. When you scan your fingerprint, your device does not need to connect with the data centre to confirm your identity. Your biometric information is on your device. Not having to rely on the bandwidth and the network for data transfer, the operation is seamless and efficient. Naturally, there are significant savings on the bandwidth costs. If we look at our autonomous vehicle example from earlier, quick decision-making is essential to prevent mishaps on the road. Edge computing will help an autonomous vehicle process sensory data in a fraction of the time, locally, when compared to having the data processed at the data centre.?

Edge computing is emerging as one of the few key technologies that will unlock the potential of future enterprise tech. However, like every other technology,?edge?computing isn’t perfect. It is why?edge?computing should be considered a complementary but essential technology to?cloud?computing. Edge?computing does well in situations where low latency is a necessity. But it also decentralises the data. That defeats the purpose of why we adopted the public?cloud. Also, the?edge is not as scalable as the?cloud, and it cannot respond to high volumes of data as quickly as the?cloud can. The responsibility of data processing should be shared between the?cloud and the?edge, depending on the critical nature of the process.?

Edge computing accelerates business innovation?

Data is the new oil; It is essential for business innovation. An organisation should be equipped with efficient storage, modern data management solutions, and powerful computing capabilities. It is why many businesses invest heavily in Big Data. But not all data that is collected and stored is essential to business development. Often,?companies end up collecting too much unrefined data and end up stretching their bandwidth costs. Not to mention the cost of storage, which increases as you scale to make room for new unrefined data. The unimportant data is discarded once the data is analysed and the business insights are extracted. Edge computing can make data management more efficient by processing the data at the?edge and transferring only the essential data to the?cloud for high-powered computing and data analysis. This saves bandwidth and helps your compute and storage resources to become more efficient. In simple terms, your compute and storage resources only handle quality data without wasting capacity on the huge quantity of data.?

Edge?computing is not only essential for enhancing?the cloud experience, but also has several uses cases for the Internet of Things (IoT). More connected devices will generate larger volumes of data. The primary function of IoT devices is to solve real-world problems. Latency can hamper the real-world experience without real-time processing.?So, edge?computing?has become?an important piece of technology for the future of enterprise tech.?

Through their alliance with us at?Vintech?Electronic Systems,?HPE equips?businesses?for?quick decision-making capabilities through faster data processing, with?AI-empowered edge computing solutions. To leverage the true power of the cloud architecture, modern enterprises need an edge to cloud support. Business agility introduces business resiliency, which is essential in today’s marketplace. With HPE’s solutions, deployed by?Vintech, businesses can prepare themselves for unexpected disruptions and reinforce their IT infrastructure. Edge?computing will be the chief driver for IoT, enabling smart cities, lights-out factories, autonomous mobility, and many such innovations. ?