ECLB: A Novel Exhaustive Criterion Based Load Balancing Algorithm for E-Learning Platform by Data Grid Technologies

Virtual learning is a method to access and share study materials for students on web. As it is the easy way of accessing data, millions of student's widely using E-learning. Due to the increase of users day by day there is an issue in scheduling and providing service to plenty of users, thus load balancing among the nodes is a great deal faced by server. This makes many research people to carry out their work in load sharing and balancing between nodes. Though the existing methods provide solution for load sharing and balancing it requires high cost. In this paper, we mainly focus on allocating loads among nodes in a network with minimum cost. K-means algorithm is used to cluster the node. Clustering increases the performance of load balancing by forming tighter clusters. To share load, among interclustering and for intra clustering we use the proposed method, Exhaustive Criterion based Load Balancing (ECLB) algorithm. The experimental results show that the load is properly and effectively shared among nodes with minimum cost.