Duncan Greatwood | Xage Security
With the recent shift to ‘smart everything’ – where things from mobile devices to light bulbs to cars are capable of connecting and transmitting data to the Internet – consumer and business expectations have changed. After so many years of rapid innovation, and the success of cloud computing, we expect networking to be faster, more secure and more interconnected than ever. However, as the number of connected, Internet of Things (IoT) devices continues to grow, the traditional model of processing information through a central cloud authority has become inefficient – and insecure. In a world where more devices than ever need to connect and securely exchange data to make meaningful decisions, local machine-to-machine cooperation and communication have become essential.
To realize this level of cooperation, computing has begun move away from the cloud to the edge. This is especially true of the computing needed for the new industrial IoT revolution, which will power the next big wave of economic growth and optimization. This IoT revolution is fundamentally distributed, requiring edge computing that shifts computing data processing, storage and services away from central servers to connected devices at the edge for local data gathering, analysis and communication. Edge computing allows for real-time or near real-time data analysis, lower operating costs, machine-to-machine-to-app cooperation without a central master, reduced network traffic and storage and optimized performance and reduced latency.
As we scramble to take advantage of these benefits, and digital innovation moves from away from the centralized I.T. cloud domain to directly impact the physical world, edge computing has the capability to reinvent everything in our world, from the way we grow our food to how we produce and deliver energy, practice healthcare and manage our buildings. And of course it is especially applicable to industrial reengineering and optimization that benefit from emerging technologies, including AI, analytics and decentralized machine-to-machine cooperation.
For example, by applying edge computing to energy production and delivery, distributed energy devices, such as smart meters, will make decisions locally and improve quality of service for customers, restoring outages in a matter of milliseconds, not hours. Within manufacturing, edge computing will create a global network to bring smart factory automation to its full potential by supporting any-to-any communication, securing user-based and machine-to-machine access to industrial systems and strengthening the network with each added device. And within transportation, a major focus in recent years, edge computing can enable in-vehicle, vehicle-to-vehicle and vehicle-to-infrastructure processing and cooperation, allowing autonomous vehicles to communicate quickly and securely with other cars.
However, while many industries are beginning to benefit from distributed and autonomous operations, it is important to remember that edge computing may not yet be essential for every business need. For many traditional I.T. activities, centralization remains strategically sound, and edge computing adoption will depend on business goals and whether a company has the resources to effectively implement, manage and monetize it.
Nonetheless, in the coming years edge and cloud computing will continue to work together to cover a broad range of requirements. For instance, while analytical processing at the edge might be used to detect anomalous behaviour and make immediate adjustments, suspected anomalies will be communicated back to the cloud for pattern-based analysis across a large number of data sets. As such, cloud computing, the essential predecessor to today’s edge computing innovation, will continue to play a role, but new use cases will make the edge the center of gravity for the next wave of technological innovation.
