As Internet of Things (IoT) devices and 5G technology become more widespread, many companies are being forced to rethink their network infrastructure. Relying on centralized cloud platforms to deliver services and analyze data creates a series of logistical problems. Data gathered on the edge of networks, where users are located, must be transmitted back to cloud servers where it must be processed before a response can be sent back to the edge. This introduces potential latency issues and creates security and downtime concerns.
Edge computing architecture, which locates key data processing functions closer to the edge of the network, offers a compelling solution to this problem. By keeping data closer to end users, latency becomes less of a problem. The increased processing autonomy of edge devices and edge data centers also reduces downtime risks, allowing users to continue using products and services even when portions of the network go down.
As new tech innovations make their way into homes and businesses in the coming years, the need for edge computing frameworks capable of integrating into a broader network will surely increase. Here are a few statistics that highlight future usage opportunities for edge computing.
Streaming content services are the future of media. Not only do nearly three-quarters of US households subscribe to a streaming service, but the average user subscribes to 3.4 of them. While the streaming market may eventually reach a saturation point, that day doesn’t seem to be approaching anytime soon. One challenge presented by all of this demand, however, is latency. Streaming services that are able to deliver uninterrupted content with minimal buffering will have a significant competitive advantage. Research has found that viewer engagement (as measured by play duration) increases as latency declines, which is in line with similar studies measuring how long website visitors will wait for content to load before leaving a site (spoiler alert: not long).
Edge computing can help streaming services improve network performance by caching popular content closer to end users in edge data centers. This is especially helpful for subscribers who live outside of major cities or near the hyperscale data centers that store much of these providers’ content. By locating high-demand media closer to users, content providers can overcome the last mile challenge and potentially take advantage of future 5g infrastructure with mobile edge computing to further enhance speed of delivery.
Self-driving cars incorporate a variety of innovative technologies that generate, gather, and process massive amounts of data. The market value for these vehicles is projected to be over $50 billion in 2019, but the potential for future growth is massive. Major tech companies and car manufacturers are investing heavily in the technology: General Motors spent $581 million to acquire a self-driving startup in 2016 while Toyota and Ford have both announced plans to invest $1 billion in AI technology.
Without some way of managing all the data they will rely on to function effectively, however, autonomous cars won’t make it far from the garage before encountering latency and bandwidth challenges. Fortunately, edge computing framework will allow them to process much of this data locally while transmitting information about road conditions and positioning to nearby vehicles. Edge data centers can handle more significant processing loads for local areas, handing vehicles off from one facility to the next while delivering additional usage and vehicle data back to the manufacturer’s central networks. The versatile structure of edge computing networks will make it possible for these vehicles to function beyond the reach of traditional cloud computing, which is essential for transportation purposes.
Connected devices are already being implemented for a variety of uses in the healthcare industry, and the market for IoT medical applications is expected to skyrocket in the coming years. From wearable IoT edge devices that gather valuable patient data to diagnostic devices designed to operate far from the reach of provider networks, these innovations have the potential to revolutionize healthcare delivery and expand services to millions of people.
Edge computing IoT will make it all possible. Not only will it empower IoT healthcare devices, it will facilitate the software applications used by telemedicine programs that allow doctors to reach previously underserved patients and provide fast, convenient evaluations over mobile devices. Data centers implementing edge architecture can also help healthcare providers and their technology partners meet the complex compliance standards that protect patient healthcare data. For all these reasons, healthcare remains one of the most exciting edge computing examples.
Although the overall market for augmented reality (AR) and virtual reality (VR) headsets declined in early 2018, industry experts expect it to not only rebound, but explode by 2022. Over the next few years, lower cost wearable devices will find their way into homes, opening up an entirely new interactive digital experience for consumers. Smartphones are already providing innovative AR experiences, but AR-enabled headsets will open up exciting new possibilities for the technology.
Without an edge computing network, however, those digital interactions will be a latency-plagued mess. A network of edge data centers will make it possible for AR devices to provide a seamless and fully-functional experience. While mobile gaming and social media apps have been the primary beneficiaries of AR technology thus far, edge computing framework will greatly improve its viability, unlocking a variety of additional applications for consumers.
Cities around the world are investing in exciting new technologies that could potentially transform their transportation and communications infrastructure. Whether it takes the form of sensors designed to regulate traffic flow to reduce congestion or more sophisticated power grids that better regulate energy usage, smart city technology will fundamentally alter the way people interact with their urban environment. Combined with other innovations like autonomous vehicles and AR devices, these applications could also be scaled far beyond their original purpose.
With so much data being generated and processed in a high-density urban environment, it’s more important than ever for cities to embrace edge computing examples that handle that data as close to the source as possible. By handling processing functions locally on IoT edge devices and through a network of micro and edge data centers, cities will be able to continuously expand functionality without overburdening their existing data infrastructure. Integrating edge computing framework will also provide these networks with unmatched versatility that allows them to adapt to changing technology and roll out new innovations as the need arises.
These edge computing statistics have only scratched the surface of the technology’s potential. As IoT devices become more common and companies feel the pressure to expand the reach of their networks, edge computing architecture will be an attractive solution, allowing them to keep their infrastructure free of unnecessary data traffic and provide faster, more responsive services to end users. As these examples show, edge computing will play a huge role in the digital infrastructure of tomorrow.