Intelligent Methods for Resource Allocation in Grid Computing
In the era of grid computing, resource allocation plays a vital role for assigning the available resources. This paper describes how to reduce the search time for the best available resources and assure instant provisioning of the lately added resources to the grid thereby using clustering and artificial neural networks. The efficacy is achieved through K-Means clustering algorithm which is used to cluster the similar type of resources on the basis of their configuration as high, medium or low thereby decreasing the search time by searching only into the cluster of high availability instead of searching for the best from all of the available resources. Thereafter artificial neural network trained with feed forward propagation is deployed to automatically assign the newly added resources to appropriate cluster.