Parallel Genetic Algorithm and Coupled Application Using Cost Optimization

Cloud Computing provides on demand access of resources over the network. The main characteristics of virtualization technologies employed in Cloud atmosphere is the consolidation and proficient management of the resources. The current work employs an optimized scheduling algorithm, which concentrates on the efficient utilization of the resources for the cloud scheduling problems. A Parallel Genetic Algorithm with the Dynamic Deme model is used for scheduling the resources dynamically. The investigation shows that the scheduling procedure improves the utilization rate of the system resources and also the pace of allotment of the resource. The user could access the computing resources as general utilities, which can be acquired and released at any time.