Abstract
IMPROVING THE EFFICIENCY OF WORKLOAD BALANCING USING CONTENT STORAGE DELIVERY NETWORK SYSTEM ON CLOUD

With the increasing demand for big data processing distributed storage systems contains number of storage nodes. Data can be equally distributed to those nodes by some techniques, such as hashing. By distributing data to different storage nodes, the load of accessing data is also distributed to those nodes, which improve the ability of big data processing in distributed storage systems. However, the load balancing mechanism based on data amount balancing is often unsatisfied. The proposed work is based on CDN(Content Storage Delivery Network) System. The scheme named as “Dynamic Flow Equilibrium” a load balancing scheme in CDN, which handles the dynamic loads and allocates the load to the appropriate content distribution server. This has been performed by receiving the customized QoS requirements of the user. QoS attributes such as time and performance of the sever. When a client request is made, the LMS (load monitoring server) and LRS (Load report Server) will perform workload identification and reports to the client, based on the current and future load, the system transmit the load to the optimal server. LMS and LRS uses bloom search algorithm to reduce the resource management cost. DFE(Dynamic Flow Equilibrium) presents a new mechanism for redirecting incoming client requests to the most appropriate server based on user customized parameters, thus balancing the overall system requests load.