Behavior pattern analysis for resource utilization in cloud computing

Analyzing the behavioral patterns to maintain the workload in cloud computing is very important. There are number of cloud data centers that have the facility to maintain this. But this paper has provided the approach for resource utilization based on two metrics, energy and cost function. This approach works within the workload which helps to understand the relationship between users and servers, and enables resource utilization, energy-efficiency improvements and cost function. From the result simulation it has been concluded that larger the number of servers or users, high will be the energy consumption but if it is optimized with an optimization method then results can be obtained in better way. So usage of multi-feedback method has also been done in work to enhance the result rates.