An Efficient Power Aware Algorithm for Optimizing Energy Consumption of Cloud Resources Using Multi Agent Model

Cloud computing offers different kinds of resources to the user based on the current need. The resource includes hardware, software and platform through virtualization. User requirements are mapped to the corresponding Virtual Machine (VM) by the host of the data center. Every resource in the data center consumed a considerable amount of energy. The existing power aware models are used to minimize the energy consumption but it follows only one specific layer in the cloud. These methods suffer from performance problems due to excess energy by the idle resources. The resources like data center, host and VM consumed energy in case of idle workload and minimum workload. Idle resources are identified and removed from the resource list in order to minimize the excess energy consumption. The resource with the minimum workload is migrated to the other suitable resources using the migration method. The proposed power aware model uses multi agent support for minimizing the energy in Data center, Host and VM level. The overall analysis is carried out based on the performance parameter like Service Level Agreement (SLA) based host shutdown and violation etc. The proposed method consumes minimum energy when compared to other existing models. It achieves maximum performance by considering power aware parameters in the cloud.