Study of Load Optimization and Performance Issues in Cloud

Nowadays, cloud computing is the latest computing platform which is feasible to the user for computation and unlimited storage and data transmission with minimal cost and time in a cloud environment during the internet. The load balancing is important criteria of cloud environment that avoid same nodes overloaded and others are idle. Ultimately load balancing can enhance the QoS parameters including make span, cost and resource utilization. To optimize the load, the existing load optimization approach is properly utilized federation mechanisms, which offers physical resources based on demand to maintain the cloud application efficiency. However, the technique failed to optimize load where part of the servers suffering from heavy load after an execution of the application. In the current scenario, several systems are facing same kinds of problem which is the biggest cause to increase the virtual machine (VM) cost. Current systems still have a time delay, request-response process error from data center side in cloud environments. To overcome these issues, the research study studies all related technique for cloud performance optimization and load balancing issues. The main framework objective is to offer an effective solution to store/search/transmit/data with minimal cost and time without compromising the QoS constraints. The study represents different policies and cloudspecific strategies to enhance the performance of cloud application with minimal cost and time. The research study is also planning to find out an effective solution for traffic, data congestion and media streaming issues in a cloud environment.