Introduction
The promise of the Internet of Things (IoT) is that it will make our world smarter. But there are significant challenges to making this work. One of those challenges is latency. Latency is the time it takes information to travel from one place to another. For example, if you’re using an app on your phone and want to know what time your preferred team plays next, you don’t want to wait for that information to travel back to your service provider’s servers and then back again. You also don’t want that information traveling across the entire internet before it reaches you. You also don’t want a delay between when a person pushes a button and when an action takes place (known as response time). Experts believe that edge computing can help reduce latency problems in IoT applications by moving some processing closer to end users’ devices or sensors.”
The promise of the Internet of Things (IoT) is that it will make our world smarter. But there are significant challenges to making this work.
The promise of the Internet of Things (IoT) is that it will make our world smarter. But there are significant challenges to making this work.
The term “Internet of Things” (or IoT) is a broad one, but it generally refers to the ability for devices and systems to connect with each other and exchange information over networks. IoT promises to make our world smarter by connecting everything from cars and home appliances to medical devices, industrial sensors and more–allowing them all to communicate with one another in real time so they can react intelligently based on their environment or situation.
One of those challenges is latency. Latency is the time it takes information to travel from one place to another.
One of those challenges is latency. Latency is the time it takes information to travel from one place to another. It’s affected by distance, network quality and other factors like weather.
In IoT, latency can be a problem because if your sensor sends data over long distances or through poor networks (e.g., cell towers), it will take longer for that information to reach its destination–and this could cause problems with your system’s response time. This is why edge computing has become so popular: because it reduces the amount of time required for data-handling tasks like data processing, analytics and machine learning at each node instead of sending all that info back up into cloud environments where these functions are performed at higher costs than they would be otherwise
For example, if you’re using an app on your phone and want to know what time your preferred team plays next, you don’t want to wait for that information to travel back to your service provider’s servers and then back again. You also don’t want that information traveling across the entire internet before it reaches you.
Edge computing allows for faster, more efficient data processing at the edge of the network. For example, if you’re using an app on your phone and want to know what time your preferred team plays next, you don’t want to wait for that information to travel back to your service provider’s servers and then back again. You also don’t want that information traveling across the entire internet before it reaches you.
With edge computing in place, this kind of data can be processed locally by sensors embedded within stadiums or arenas–and sent directly from there into the cloud. In turn, this means less latency when accessing content like sports scores or weather reports while out in public spaces like stadiums or parks–or even restaurants!
You also don’t want a delay between when a person pushes a button and when an action takes place (known as response time).
In the world of smart IoT devices, response time is the time it takes for an action to be completed. It’s important because it affects the user experience and can be improved by reducing latency.
For example: You don’t want a delay between when a person pushes a button and when an action takes place (known as response time). If this delay gets too long, they’ll get frustrated with your product and stop using it–or worse yet never even try it in the first place!
Experts believe that edge computing can help reduce latency problems in IoT applications.
Edge computing is a way to reduce latency in IoT applications. It can be used to process data locally, in real time, or near real time (or even near-near real time).
Experts believe that edge computing will make the world a smarter place by enabling faster decision making and improving efficiency.
Conclusion
The promise of the Internet of Things (IoT) is that it will make our world smarter. But there are significant challenges to making this work. One of those challenges is latency. Latency is the time it takes information to travel from one place to another, which can cause problems for IoT applications like smart cars or home monitoring systems. Experts believe that edge computing can help reduce latency problems in IoT applications by processing data close to where it’s generated rather than sending everything back to a central location first
