The Online Control Framework on Computational Optimization of Resource Provisioning in Cloud Environment

Abstract

The resource monitoring and management system for data center are capable of huge amount of activities. In terms of resource allocation and workload using a variety of K-means clustering algorithm. Workload and machine heterogeneity as well as an optimization problem that is described to see that considers reconfiguration costs. It will solve the problem by using control framework based on computational optimization algorithm. More efficient transfer of energy consumption and delay between each machine by using scheduling algorithm. Energy consumption characteristics of the various machines provide different capacities. Cloud data center are capable of sensing the machine and power consumption. In my proposed using the hybrid method for resource provisioning in data center. This method is used to allocate the resource at the working condition and also energy stored in the power consumption. Keywords: Cloud Computing, Dynamic Capacity Provisioning, Machine Heterogeneity, Resource Monitoring