Edge computing is powering many of the world’s latest innovations — like the Internet of Things (IoT), autonomous vehicles, remote sensors, remote surgeries, augmented reality (AR) and 5G. These technologies require essential capabilities, like the ability to process and analyze vast quantities of data in real-time to produce actionable insights.
But these technologies can’t perform optimally living only in the cloud. They work best living on the edge.
Edge computing entails capturing and processing data as close to the source as possible. With edge architectures, compute and storage systems reside as closely as possible to the components, devices, applications and humans that produce and use the data.
This proximity removes processing latency by reducing the distance that data must travel. Data no longer has to be sent from the edge of the network to a central processing system, and then back to the edge. For example, to replace human drivers, autonomous driving technologies must reduce the 100 milliseconds that it takes for data transmission between vehicle sensors and backend cloud datacenters. Only the edge can overcome this challenge.
Data Drives Devices to the Edge
Although it’s hovered around the edges of the computing world since the 1990s, edge computing is coming into its own. And it’s just in time to meet the needs of a world filled with new data-rich applications being used in many industries — a trend that’s expected to continue.
IDC predicts that by 2025, there will be over 150 billion machine sensors and other connected IoT devices streaming data continuously. Further, IDC says that edge computing is poised to be one of the main growth engines in the server and storage market for the next decade and beyond.
The advent of 5G networks, which are expected to be 10-times faster than 4G, further increases the need for speed. Edge computing supports more sophisticated applications, especially those that need to overcome latency and bandwidth limitations. It eliminates long distances between devices, bringing the power to them wherever they run.
Organizations that have already embraced edge computing are gaining several significant advantages, including:
- Real-time responsiveness — As the volume, variety and velocity of data from more connected devices increases, localized network resources deliver real-time value by enabling faster interpretation and processing.
- Reliability — The edge delivers reliability in a world where different devices have different requirements for processing power, electricity and network connectivity.
- Cost efficiency — As data moves faster, decisions can be made faster, which can help reduce costs. Also, the reduced reliance on centralized data processing in the cloud can curtail network overhead costs.
One key area of weakness in edge computing can be data security. The problem stems from the wide range of devices used with a secure centralized or cloud-based system. This issue can be exacerbated with the use of IoT devices, which have a documented history of being points of vulnerability in network security. However, distributed network architectures make it easier to lock down and isolate compromised system components, and also reduces the volume of data at risk at any given time.
Retail’s Future on the Edge
Retail is a prime example of an industry that is poised to rapidly embrace life on the edge — and it serves as the perfect use case for what is possible in every industry. Retail directly impacts people’s lives in multiple ways. Today’s consumers have high expectations, including convenience, superior customer service and better shopping experiences, requiring retailers to find new and engaging methods through innovation to maintain and grow brand equity.
Retail is a prime example of an industry that is poised to rapidly embrace life on the edge.
Research by MarketsandMarkets predicts that retail will be the fastest-growing segment of the edge computing market largely due to the high volumes of data generated by IoT sensors, cameras and beacons that feed into smart applications. Edge computing will allow this data to be more efficiently collected, stored and processed than is possible in the cloud or an on-premises data center.
While this prediction was made before the COVID-19 pandemic, there is still a great opportunity there. In fact, retailing innovations supported by edge computing, especially those impacting the customer experience, could help to revive the industry when things return to normal — or, in this case, the “new normal” for retailing.
Here are just a few examples of innovations poised to dominate the retail sector of the future:
- Point-of-sales systems linked to tablets that let associates process transactions anywhere on the sales room floor.
- Barcode tags that shoppers can scan with their smartphones to capture product information on the spot.
- Smart fitting rooms equipped with AR mirrors that display outfits in different clothing without physically trying them on.
- WiFi systems that recognize consumers and deliver personalized product offers in real-time.
- Infrared beacons that generate heat maps that tell retailers about in-store traffic patterns, allowing them to better design their spaces.
- Digital synchronization between in-store, online and mobile experiences to boost customer loyalty and attract new customers.
Some of these innovations are already in use. One example is the “mini Tesco” grocery stores in the United Kingdom and Ireland. These smaller regional stores are finding success by delivering a higher degree of personalization through their product offerings and promotions. In order to do that, stores must have a clear understanding of local consumer demand and knowledge at the micro level of which products are selling and which promotions are appealing. This impacts everything from product placement to the supply chain. As a result, with data and analytics closer to home, they can deliver exactly what their local customers want.
The Race to the Edge
Nearly every industry has deployed or is developing technological innovations that can only be successful if they are supported by edge computing. The edge could improve business operations in a number of ways, such as supply chain efficiency, machine maintenance and data optimization. A few examples of use cases from three industries include:
- Supply chain sensors in healthcare manufacturing — A shipment of temperature-sensitive pharmaceuticals could be monitored from the time it leaves the factory until it reaches the pharmacy.
- Predictive maintenance in manufacturing — With edge computing, IoT sensors can monitor machine health and identify signs of time-sensitive maintenance issues in real-time.
- Fleet management — Efficient means of network transmission can maximize the value potential of fleet telematics data for vehicles traveling to distant locations.
All of these innovations and others are fueling the rapid growth of edge computing in nearly every industry. Before COVID-19, the research company predicted that the edge computing market size would grow from $2.8 billion in 2019 to $9.0 billion by 2024. Key factors driving the edge computing market have included the growing adoption of IoT across industries, the rising demand for low-latency processing and real-time decision-making solutions, the need for surmounting exponentially increasing data volumes and network traffic and, of course, the expansion of 5G deployments.
The reality is that no one can put data centers in every region to meet increasingly localized power demands.
Going forward, more organizations will be assessing the potential to leverage edge computing to meet their specific needs. The reality is that no one can put data centers in every region to meet increasingly localized power demands. Edge computing enables us to leverage the fullest capabilities of today’s leading-edge innovations closer to the tools that need them.
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