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With the continuous adoption of cloud computing, mobile network, big data, and SDNs, the number of internet users has exploded. To catch up to the fast-changing trends with wireless connectivity and the internet, companies have strived to have more cloud adoption for different business operations. Cloud computing for years has offered a secure and controlled way of reliable remote access. However, it does lack the speed to process the gathered data from the edge of the network, which is a point where an enterprise owned network connects to a third party network. This challenge, in recent years, is addressed by edge computing as it offers better latency.
Below we look at some differences between edge computing and cloud computing and whether it can replace cloud computing.
IT can also be described as a distributed IT network architecture that enables mobile computing for locally produced data. So, instead of sending the data to the computer science vs information technology power to ensure real-time processing without latency in addition to reduced storage and bandwidth requirements on networks.
For a good example, consider autonomous cars. For any autonomous cars, road safety is the most critical aspect of driving. These autonomous cars in order to drive safely must be able to recognise obstacles or people in real-time and hit the brakes if there is something in its path. This will require visual processing information and making decisions quickly, which is done using edge computing. It takes around 100 milliseconds for the data to be transmitted between the car’s sensors and cloud data centres, this figure might seem fast, but in driving, it isn’t. This delay or the time for data transmission has a significant impact on the reactions of self-driving cars. Edge computing, in contrast, expedites the process and reduces the load on networks to help improve the autonomous car’s performance. Here, speed becomes one of the critical highlights of technology like edge computing.
Below we look at some differences between edge computing and cloud computing and whether it can replace cloud computing.
IT can also be described as a distributed IT network architecture that enables mobile computing for locally produced data. So, instead of sending the data to the computer science vs information technology power to ensure real-time processing without latency in addition to reduced storage and bandwidth requirements on networks.
For a good example, consider autonomous cars. For any autonomous cars, road safety is the most critical aspect of driving. These autonomous cars in order to drive safely must be able to recognise obstacles or people in real-time and hit the brakes if there is something in its path. This will require visual processing information and making decisions quickly, which is done using edge computing. It takes around 100 milliseconds for the data to be transmitted between the car’s sensors and cloud data centres, this figure might seem fast, but in driving, it isn’t. This delay or the time for data transmission has a significant impact on the reactions of self-driving cars. Edge computing, in contrast, expedites the process and reduces the load on networks to help improve the autonomous car’s performance. Here, speed becomes one of the critical highlights of technology like edge computing.
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