Presenting a Method for Predicting Content Error in Cloud Computing Using the Nearest Neighbor Method
Abstract
Cloud computing is a new technology for managing and providing services over the Internet. Cloud computing is a large group of connected computers. These computers can be personal computers or network servers. They can also be public or private. The prediction of content error is one of the fundamental challenges in cloud computing. In this research, it was tried to increase the accuracy of prediction error of content in cloud computing using the nearest neighbor algorithm. The simulation results in MATLAB software showed that the method for the data set had a very high performance. The results were compared with the performance of three perceptron neural networks based on radial performance and nearest neighbor. Finally, the best combination among these systems resulted in the nearest neighbor error detection with nearly 74% accuracy.