Processing and data storage take place on edge systems via the cloud. But network restrictions can be the best way to differentiate edge from cloud.
At its core, the main difference between edge computing and cloud computing lies in one concept: network connection limitations. If internet connectivity were always available everywhere and data could be transferred instantly and without delays, there would be no need for edge computing solutions. However, because network connections are neither constant nor ubiquitous, and both bandwidth and latency are limited, edge computing solutions have emerged to address each of these issues.
Cloud computing allows users to access processing power and data remotely via an Internet connection. For most purposes, users can pretend that computing power and disk space are infinite, even when computing capacity is actually constrained by a finite number of data centers. Do you need more computing power? Spin up more servers. Would you rather keep more photos, files or other data? Provide larger storage limits.
The rise of reliable internet connections and cloud computing has been roughly synchronous since the early 2000s. The nature of the data transmitted also changed over time, gradually evolving from an emphasis on text and compressed images to audio and live-streamed video.
For businesses, this meant that file servers that were formerly on-premises could be moved to the cloud. Cloud computing companies often offered levels of reliability and redundancy that easily exceeded what most IT departments could offer.
Cloud applications have brought both power and ease of management to more businesses. For example, responsibility for updates has shifted from HR administrators to cloud providers. For example, new features appear in Google Docs when Google rolls out a change, without the need for on-site admin intervention.
Many school systems that are chronically resource-constrained have switched to Chromebooks because the cloud-centric computers are easier to manage, maintain, and secure than most legacy server-centric systems.
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Two niche segments – large providers of interactive websites and streaming services – provided the first indications that a significantly different computer architecture might be required. In particular, these companies have recognized that data transmission to individual customer computers takes time. Content delivery network providers began moving data centers closer to consumers (Figure A).
For example, a person streaming a movie in Michigan will likely experience lower latency if the streaming source is a data center in Chicago compared to Los Angeles. Vendors today use the term “edge” for smaller data centers of varying sizes, but all are trying to solve the network connection limitation of distance-induced latency.
With the use of connected home technologies, another class of edge computing emerged. Users want smart locks, security cameras, and various environmental sensors to work even when Wi-Fi goes down, a cable gets cut, or cellular networks stop working temporarily.
Eventually, vendors started building systems that communicate using different standards like Bluetooth, Zigbee, and Matter. Similarly, machines in an industrial environment may need to operate in environments without reliable networks. Since almost all of these smart home and industrial devices generally remain stationed in a single location, the constraint on the network connection they address is a temporary lack of connectivity.
However, moving vehicles — on land, in the air, and at sea — represent many of the most challenging edge computing tasks yet.Figure B), but their movement speed often doesn’t leave enough time to rely on long-distance calculations even when linked. In other words, by the time a speed-autonomous car may receive a response from a nearby cloud data center about a road hazard, the car may already have encountered it.
Regular connectivity for these types of vehicles remains critical. Cars and trucks, for example, benefit from updated maps showing roads, construction sites and current traffic conditions. Drones and autonomous ships rely on weather data to identify potentially turbulent skies or seas.
People managing these devices will likely want to offload data not only to evaluate and improve performance, but also to retrieve images and other information captured by the vehicle’s various instruments. Edge systems that enable this type of autonomous operation and intermittent network connectivity present several challenges that remain unresolved by the end of 2022.
What’s your experience?
Cloud computing makes it possible to use computing power and storage space wherever there is a reliable internet connection. Edge computing shifts processing and storage from these cloud data centers to devices that can compute independently of a constant connection.
Do you use a mix of cloud and edge computing systems in your work? Are there specific edge computing capabilities not mentioned above that you find helpful in your environment? What types of management and governance systems have you deployed to manage your organization’s cloud and edge computing systems?
Mention or message me on Twitter (@awolber) to let me know what your experiences are with edge computing—and which edge computing technologies you’re watching most closely.