Edge computing is also known as distributed computing as it brings up the computation and data storage closer to the networks. This will improves the response time to save bandwidth. Edge computing is simply works as a computer program for the lower latency of data in the network.
In the modern scenario edge computing extends its path through virtualization technology which makes easier to run the wider range of applications depending on the edge server. Edge nodes are used in the network to hop-up the client in the real-time applications.
The massive amount of the IoT devices is producing data to the computer under the edge computation in the networks. The main aim of Edge computing is to provide the smart way of computations to the smart objects, mobile over the edge of the network. New challenges and issues also occurred due to distributing the logic at different network nodes.
In the distributed network it faces some issues in different forms. The security requirements will introduce the latency between the nodes in the communication pathway, so this may low down the scaling process.
The network topology is introduced in the system so that it could detect the errors at the each edge of the network. This is done due to the problem raised as if any of the singles goes down and cannot be re-contained again, then this will reliable to solve the issue with several levels of data transferring.
Computational analysis are brought to the end users by the edge of computational data, This will speed up the communication as it would also perform the cloud-computing system.
Artificial intelligence is also added up with the computing to develop the efficiency of the computing system and also brings lots of advantages in the communication system
Cloud Computing vs Edge Computing:
Cloud Computing is used for the lots of data operated on the system while Edge Computing is used in the operations where instant data is required.