Data centers have become an indispensable part of modern computing infrastructures. It becomes necessary to manage cloud resources efficiently to reduce those ever-increasing power demands of data centers. Dynamic consolidation of virtual machines (VMs) in a data center is an effective way to map workloads onto servers in a way that requires the least resources possible. It is an efficient way to improve resources utilization and reduce energy consumption in cloud data centers. Virtual machine (VM) consolidation involves host overload/underload detection, VM selection, and VM placement. If a server becomes overloaded, we need techniques to select the proper virtual machines to migrate. By considering the migration overhead and service level of agreement (SLA) violation, we investigate design methodologies to reduce the energy consumption for the whole data center. We propose a novel approach that optimally detects when a host is overloaded using known CPU utilization and a given state configuration. We design a VM selection policy, considering various resource utilization factors to select the VMs. In addition, we propose an improved version of the JAYA approach for VM placement that minimizes the energy consumption by optimally pacing the migrated VMs in a data center. We analyze the performance in terms of energy consumption, performance degradation, and migrations. Using CloudSim, we run simulations and observed that our approach has an average improvement of 24% compared to state-of-the-art approaches in terms of power consumption.