Introduction
The term edge computing is a broad one, encompassing the entire ecosystem of hardware and software that allows data to be processed at the network’s edge. A more specific definition would be a subset of cloud computing: servers and related systems that help businesses improve their productivity by processing data locally instead of sending it all the way back to headquarters for processing.
What is Edge computing?
Edge computing is a type of distributed computing that occurs at the edge of a network. The term “edge” refers to the place where data enters or exits a cloud system, such as a mobile device or computer. Edge computing is also known as fog computing and fog networking (because it sits between cloud systems and devices).
Edge computing can be used for real-time analytics, which means companies can process data at the point of origin instead of having to send it back to central servers first before they can analyze it there. This improves efficiency and reduces latency–a measure of how long it takes information to travel from one place to another–by reducing travel time by milliseconds or seconds in some cases!
The benefits of edge computing
Edge computing is a new way of doing things, and it has the potential to dramatically change how we work. It’s a way of taking the load off the cloud and putting it on your own hardware, at least temporarily.
Edge computing improves efficiency by allowing you to do more with less; if you have an edge computing solution in place, then there are no limits on what can be done remotely or locally–you can use whatever resources are available at any given time.
Edge computing improves security by making sure that sensitive data never leaves your premises unless absolutely necessary (and even then only after being encrypted). This prevents breaches like those seen with Equifax or Yahoo!
Challenges with edge computing
As you can see, edge computing comes with some challenges.
There are three main challenges that come with edge computing: data latency, security and privacy. Data latency refers to how long it takes for information to be transmitted from one place to another. In traditional cloud-based systems, this is not an issue because most of your data stays in the cloud where there are high bandwidth connections and powerful servers that can handle large amounts of traffic at once. However, when dealing with devices at the edge (which may have limited storage capacity), there will be times when these devices cannot process all their information immediately due to lack of resources or simply because they don’t have access to internet connections yet–and this could lead back towards centralization since there’s only so much local storage space available before needing more room than what was intended for just one user/company/etcetera.”
A definition of edge computing, as well as its benefits and challenges
Edge computing is a new approach to data processing and storage that moves data closer to the source. It allows organizations to collect, process and analyze information at the place where it originates. The concept of edge computing can be applied in many industries, such as IoT (Internet of Things), autonomous vehicles and robotics.
Edge computing has many benefits over traditional cloud computing models: faster response times, lower latency and improved security are just some of them. However, there are also challenges associated with this approach such as limited resources on-premises or high costs for deploying equipment close to users’ locations
Conclusion
Edge computing isn’t a new concept, but it’s one that we’re seeing more and more in today’s world. As the Internet of Things continues to grow, more people will be looking for ways to connect their devices with one another as well as with other systems like databases and servers–and this requires some type of solution that can handle all those requests at once without slowing down. Edge computing offers just such an option: by using local processing power instead of sending everything off-site where it could take hours or even days before returning results back to your device (or whatever else needs access), this new technology allows users to make decisions without waiting around too long before getting results back from elsewhere
