Balancing workload based on content types for scalable Web server clusters

With the rapid growth of information stored in worldwide Web servers, searching and capturing data on Internet become a common behavior for us. In order to increase the availability as well as avoid the overload of the single Web server, using Web server cluster is one of main solutions. We take the contents/services types into consideration for balancing workload of Web servers. For different contents requested by clients, the workload for each Web server would be different. Hereby, we focus on proposing a new load balance algorithm for supporting fast response and load balancing for scalable Web server clusters. In addition, we demonstrate our simulation experiments to show that our proposed approach, as compared to existing approaches. This proposed approach can be applied to various applications, especially for resolving e-learning systems with needs of a great deal of requests with different service types simultaneously issued by worldwide users.