Although today’s consumers are generally aware of the benefits of cloud computing, edge computing hasn’t quite captured the public consciousness in the same way. But as Internet of Things (IoT) devices enter the market in record numbers and consumers demand more of their network services, edge computing framework is already having a big impact on how companies meet the needs of their users. Fortunately, the basic definition of edge computing is quite straightforward.
Edge computing pushes key data processing functions away from centralized cloud servers and closer to the edge of the network where users are located. By reducing the distance data has to travel for processing, edge computing frameworks can greatly enhance IoT device functionality and provide much faster services than conventional networks. Building this type of framework may seem like a huge challenge, but organizations can get started on the right track by addressing a few major criteria.
The first step in building any edge computing framework is assessing what it needs to do and who the end users will be. There are many different edge computing use cases and examples. A streaming content provider, for instance, needs an edge network that allows it to deliver large amounts of data with minimal disruption, but it doesn’t need to account for and manage the massive quantities of data being generated by an autonomous vehicle. While edge computing principles can be applied to a variety of situations and use cases, there is a lot of variation in terms of what kinds of data need to be processed and how quickly. Different users will have different needs as well. A factory utilizing industrial IoT sensors, for instance, will be more concerned with how data is gathered and sorting out what data needs specialized processing than a field repair technician using and IoT scanner to access data remotely. Identifying the specific needs of each use case will help organizations build edge computing frameworks optimized for superior performance.
Since edge computing shifts key processing and data collection functions to the edge of the network, connectivity options are an important consideration. While 5G networks are becoming more common and could potentially push edge computing to the next level, this groundbreaking technology won’t be available in every market. In many cases, “last mile” connections will introduce significant latency into networks, forcing companies to think about how to push processing functions even closer to their end users. A good edge computing framework must have the versatility to accommodate multiple forms of connectivity and account for a variety of IoT devices that are already in service or could be in service in the future. In rural and underserved areas, IoT devices may need the capacity to function independently until they can be reconnected to the edge network. Designing a flexible system that can account for these factors is critical to any edge computing framework.
In almost any use case, a versatile edge computing framework will make heavy use of edge data centers. These facilities can play a number of roles in network architecture, sometimes providing extra processing resources closer to the edge and at other times facilitating content delivery to minimize latency. Edge data centers are often much smaller than enterprise facilities and are more oriented toward servicing the internet needs of a local market. They are optimized for speed with high-capacity routers and must have high levels of uptime reliability. Building an edge computing framework that incorporates unreliable data centers is a recipe for disaster in the form of frequent downtime events. Whether it’s a regional facility located in an emerging market or a portable micro data center, identifying local data centers that can enhance the processing capabilities of the network edge is vital to building a powerful edge computing framework.
Edge computing presents a unique set of security challenges compared to traditional, centralized cloud networks. The increased surface area of the network and the high level of connectivity translates to additional attack vectors for hostile actors. With so many IoT devices accessing the network edge, it’s critically important for companies to protect their data and core systems from unauthorized access. Encryption protocols and enhanced monitoring of data center assets are a good first step, but edge computing networks also need to be designed with a “low trust” philosophy that automatically assumes that every device connecting to the network is already compromised in some way. While this can cause some inconvenience, forcing every access request to undergo some form of authentication is the best way to keep the network edge secure and safeguard organizations from compromising (and expensive) data breaches.
As IoT devices become more common and more users consume digital media via “on-demand” services, companies need to put a great deal of thought into the design of their edge computing framework. By constructing edge architectures that are optimized around their specific products and services, organizations can better serve their users with minimal latency and consistent uptime without compromising data security. Edge data centers will play a crucial role in these networks and help to extend services to new users in previously underserved markets.