Introduction

The term “edge network” refers to the location of data in a network. When your data lives at the “edge” of a network, it means that it’s closer to the end-user than if it was stored centrally. In other words, edge computing is all about making sure your data is as close as possible to where it’s needed. This can be especially important when it comes to applications like mobile gaming or video streaming, which require faster processing speeds and more accurate decision-making capabilities than centralized cloud services provide.

Edge computing is a term used to describe the practice of processing data at the edge of a network, instead of centralized cloud computing systems.

Edge computing is a term used to describe the practice of processing data at the edge of a network, instead of centralized cloud computing systems. The term “edge” comes from mapping the internet to a graph where nodes represent devices (computers, smart phones) and edges represent communication between the nodes.

Edge computing can be implemented on any device or system that has access to both network connectivity and data storage capabilities. This includes things like smartphones or smart home appliances–but also includes traditional servers inside private networks if you want them too!

Edge is defined by where your data lives in the network.

Edge is defined by where your data lives in the network.

  • Edge is where your data lives. It’s the collection of devices, small and large, that are connected to each other via the internet and can communicate with each other directly or through a central hub (like an application server).
  • Edge is where your data is processed. When a device collects information about something happening in its environment (for example, temperature readings from sensors), it uses AI algorithms to process this information into useful insights for its owner–that’s called processing at the edge because it happens directly on that device without needing any additional computation from anywhere else on earth!

The term “edge” comes from mapping the Internet to a graph where nodes represent devices (computers, smart phones) and edges represent communication between the nodes.

The term “edge” comes from mapping the Internet to a graph where nodes represent devices (computers, smart phones) and edges represent communication between the nodes. In this context, edge computing is simply the practice of processing data at the edge of a network, instead of centralized cloud computing systems.

Edge computing can be implemented in any number of ways depending on what you are trying to accomplish with your data processing needs. For example:

  • If you have large amounts of video footage that needs transcoding before being sent over the internet–you could use an edge computer like AWS DeepLens which allows users to run machine learning algorithms directly on their camera’s hardware rather than uploading it all into Amazon’s cloud first
  • If you’re looking for more advanced features like facial recognition or object tracking–this type of functionality would likely require something like Google Cloud Vision API which provides image analysis capabilities

By bringing together multiple pieces of information, an edge server can make complex decisions in real time without having to send individual requests back to central servers or data centers.

Edge computing is the concept of running applications and storing data at the edge of a network, close to where it’s needed. This allows for faster responses to requests, reduces latency in processing, and can help companies make more informed decisions about their operations.

In order to understand how edge servers work, let’s take a look at what they’re made up of:

  • A server that runs software as well as hardware components such as microprocessors or graphics processing units (GPUs). These are all connected together in one place–either on-premise or in the cloud–and act as a central hub for all other devices within an organization’s network infrastructure.
  • An edge server differs from traditional web servers because it doesn’t have access to all of your data; instead, only relevant information gets passed back down through its own internal network connection before being delivered directly into your browser window via HTML5 protocol (Hypertext Markup Language Version 5).

Edge computing is being deployed by companies like Microsoft, who see it as an alternative to centralized cloud services that require high bandwidth and latency for low-bandwidth applications such as mobile gaming.

Microsoft is one of the leading edge computing providers, and it’s been using the technology to improve its cloud services. Edge computing allows companies like Microsoft to improve performance by moving some processing from centralized data centers closer to users who need that information. This is especially important for mobile gaming applications, which require low bandwidth and latency.

Microsoft sees edge computing as an alternative to centralized cloud services that require high bandwidth and latency for low-bandwidth applications such as mobile gaming

Edge computing allows for faster processing speeds and improved decision making capabilities at a fraction of the cost.

Edge computing is a more cost effective solution for companies with low bandwidth applications. Edge computing allows you to process data at the edge of your network, which means it can be done faster and at a fraction of the cost of traditional cloud-based solutions.

Edge computing is also a more secure solution for companies with sensitive data that needs to be kept private and secure from hackers or misuse by employees. By keeping all of your sensitive information on an isolated network where only those who need access have access, you can ensure that users won’t accidentally leak information that should be kept private like bank account numbers or medical records (or even worse).

Conclusion

Edge computing will be a major driver of innovation in the coming years. Its ability to process data at the edge of a network and make real-time decisions without sending individual requests back to central servers or data centers is already proving its worth in sectors like gaming, where latency is critical and bandwidth requirements are low. But with more devices connected online every day, we can expect this trend to continue growing as well–and who knows what new applications might emerge from there?