What Is Edge Computing & How Does It Reduce Latency

What Is Edge Computing & How Does It Reduce Latency

Introduction

Latency is one of the most important metrics for any application. It’s an indication of how long it takes for data to travel from point A to point B and back again. You can reduce latency by moving your application closer to the user or by reducing the distance between them. Just like a race car driver will use every trick in their arsenal to shave off tenths of a second, computing professionals must do everything they can to minimize network latency between servers, applications and end users. In this post we’ll explore what edge computing is and how it can reduce latency for your applications

What is Edge Computing?

Edge computing is a technology that allows data to be processed at the edge of a network, or as close to where it’s being used as possible. This reduces latency and improves performance for many applications.

Benefits of Edge Computing:

  • Reduced Latency – Because data processing takes place closer to where it’s being used, there are fewer steps between sending and receiving data. This means less time spent waiting for information to travel across networks, which translates into lower overall latency for your app or website users (and faster response times).
  • Improved Reliability – Data can also be stored locally so if there’s an issue with your internet connection or another part of your system, you’ll still have access through local storage options such as hard drives or USB flash drives (or even just printed paper copies).

Latency Reduction in the Cloud

Edge computing is a term that refers to the process of moving data processing from centralized cloud servers (i.e., the “cloud”) to devices on or near your network. This can be accomplished through various methods, including:

  • Edge device management software that allows for remote access and control of hardware devices like routers and switches;
  • Data analytics software that processes data at the edge node rather than sending it back to a central location for processing; and
  • Serverless computing platforms that run applications locally on end-user devices instead of having them run on servers in a remote data center.

Remote Training Solutions

Remote training solutions are another good use case for edge computing. As with other IoT applications, latency is the primary concern when it comes to remote training solutions. The goal of these systems is to provide a continuous learning experience by connecting students and teachers in real-time over long distances.

The use of edge computing can help reduce the latency issue associated with these types of systems, but there are still some challenges that need to be overcome before we’ll see widespread adoption among educational institutions:

Connected Cars and Edge Computing

As cars become more connected, the demand for real-time data processing is growing. For example, a connected car might be able to use edge computing to reduce latency by processing sensor data at its source rather than sending it back to the cloud.

What Is Edge Computing?

Edge computing is an IT architecture that uses local resources to process data instead of sending it all the way back down to central servers in the cloud. This can improve performance because there’s less distance between computers and their applications (or “edge devices”), which means less time will be spent traveling between those points over your network connection–and less time means less latency!

How Does It Work?

In order for this approach to work, you need two things: a wireless network connection and some kind of local resource like an IoT device or computer with enough power and storage space on board so that it doesn’t need constant updates from other systems across great distances every few milliseconds while trying not only run but also analyze various types of information simultaneously while still remaining secure enough not get hacked into easily by malicious hackers looking specifically after those same kinds off opportunities where they could potentially gain access without anyone noticing until too late anyway…

Industrial IoT and Edge Computing

In industrial IoT applications, edge computing has been used for years. For example, a factory may have hundreds of sensors that measure temperature and pressure inside pipes. If these sensors were all connected to the cloud, it would take time for each piece of data to travel back and forth through the internet before being processed by an algorithm. This would cause a significant delay in processing time–enough time for some fluids (oil or water) in those pipes could leak out due to the high pressure inside them!

By using edge computing instead of sending all your data straight up into the cloud, you can save yourself from this problem by having all your sensor readings sent directly from each sensor directly into your computer at work or home where they’ll be analyzed immediately without any lag time between receiving information from one place versus another.”

How does Edge Computing reduce latency for your application?

You may have heard of edge computing, but you might not know exactly what it is. Edge computing is a new way of thinking about how we distribute and process data in our applications. It allows us to move the processing closer to where the data source resides, which significantly reduces latency for your application.

Edge Computing vs Traditional Cloud Computing

Conclusion

By now, you should have a good understanding of what Edge Computing is and how it can help reduce latency for your application. It’s important to remember that Edge Computing is not just for IoT devices or remote training solutions–it can be used in any industry where there’s a need for real-time data processing at the edge (or near) of the network. The ability to process data locally means less bandwidth consumption on traditional cloud servers, which will ultimately lead to lower costs for businesses who adopt this technology!

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