The amount of data that needs to be transported, the resulting traffic, and the distance that data must travel are all reduced by Edge Computing Application services. This lowers latency and lowers the cost of transmission. Early studies revealed that computation offloading significantly improved response times for real-time applications like facial recognition systems. Further study revealed that when some of the jobs are delegated to the edge node, using resource-rich devices termed cloudlets or tiny data centers close to mobile users, which offer services generally found in the cloud, produced gains in execution time.
On the other side, offloading every task could cause a slowdown owing to transfer durations between devices and nodes, therefore an ideal configuration can be determined depending on the workload.
The power grid may be monitored and controlled using an IoT-based power grid system, which improves the effectiveness of energy management.
Another application of the architecture is in cloud gaming, where some game components might run in the cloud while the produced video is sent to lightweight clients operating on mobile phones, VR headsets, and other devices. Pixel streaming is another name for this kind of streaming.
Other noteworthy uses include home automation systems, connected and autonomous vehicles, smart cities, and Industry 4.0.
There was initially One Big Computer. Then, during the Unix period, we learned how to use simple (not derogatory) terminals to connect to that computer. Personal computers came next, marking the first time that common people actually possessed the equipment that performed the work. We are fully in the cloud computing era as of right now, in 2018.
Most of us still use our personal computers to access centralized services like Dropbox, Gmail, Office 365, and Slack, but this is the only reason why many of us still own them.
