Edge computing and distributed computing are two of the most talked about buzzwords in technology today. But what do they mean, and how can they be used together to take your business to the next level? In this blog post, we will explore the definitions of both terms, discuss how they can be used together, and provide examples of businesses that are already taking advantage of this powerful combination.
What is distributed Computing
Distributed computing is when many computers work together to figure out difficult things. This is different from traditional computing where only one computer does everything. In distributed computing, the work is shared between all the computers. When doing a complex task, it can be split into smaller pieces. Each piece is given to a different computer. The computers work on their part and then the results are put together to make the final result. This makes things faster and better, so many companies use this way of working.
What is edge Computing
Edge computing is a way to take distributed computing one step further. It allows the computation to be done closer to where the data is being collected. This reduces latency and energy use, which makes it much more efficient than traditional cloud-based solutions. Edge computing also enables businesses to process large amounts of data quickly and securely without sending it over long distances.
The difference between Edge vs Distributed Computing
Edge computing is a method of handling data near where it originates like from a sensor, device, or endpoint. This helps reduce the amount of data that needs to be transferred over the network by processing it locally and only sending the necessary information to a central location. Edge computing is particularly beneficial in situations requiring low latency, such as autonomous vehicles or industrial automation.
In a distributed computing environment, data may be distributed across multiple servers or devices, but the goal is still to keep the processing as close to the data source as possible. The distributed servers or devices work together to process the data and generate results, but the data does not necessarily need to be transferred to a central location before processing.
So, both edge computing and distributed computing can be used to achieve decentralization, but they do so in different ways. Edge computing keeps data processing close to the source, while distributed computing spreads processing tasks across multiple servers or devices.
Is distributed computing used in combination with edge computing?
Using distributed computing with edge computing can enhance the computing infrastructure and provide better outcomes. It’s common to use both edge and distributed computing together.
In edge computing, a sensor can gather a lot of data that must be processed promptly for instant decision-making. To accomplish this, a distributed computing framework can distribute the processing workload between several servers or devices near the sensor. This process reduces processing time and guarantees that real-time outcomes are obtained.
Distributed computing can improve fault tolerance in edge computing situations by dividing the processing load between multiple servers or devices. This approach ensures that the system remains operational even if some of the servers or devices fail. Implementing distributed computing with edge computing can lead to a more effective and resilient computing infrastructure that can cope better with the requirements of today’s applications and services.
Uses for Edge Computing and Distributed Computing
Distributed edge computing and edge computing are versatile technologies suitable for various applications, including gaming, IoT, and autonomous vehicles. They simplify complicated tasks and enhance efficiency. Additionally, they can conserve energy and reduce power usage, making them environmentally sustainable.
To accurately predict events on the road, self-driving cars require AI processing. Distributed edge computing enables faster and more precise processing of this data, helping to enhance safety and decrease the likelihood of accidents.
To minimize the lag time for end users, businesses can utilize edge computing and distributed computing by operating applications across multiple edge nodes. This ensures the availability of their services at all times.
Conclusion
Distributed computing and edge computing go hand in hand. By using distributed computing, businesses can split up the data processing task into smaller parts that can be processed by multiple computers at once. This makes it faster and more efficient than traditional cloud-based solutions, but with edge computing these tasks can be done even closer to where the data is being collected. By using both distributed and edge computing, businesses can process large amounts of data quickly, securely, and with minimal lag time.
You may also be interested in The Difference between Parallel and Distributed Computing.
