In cloud computing, to achieve proper load balancing, the cloud data center dynamically migrates and deploys VM to meet user’s requirements without degrading the service being delivered to the user. Several migration techniques are available for migrating VM from one host to another. But they fail to consider the migration cost while determining the energy consumption during migration. One of the options to reduce the power consumption of data centers is to reduce the number of idle servers, or to switch idle servers into low-power sleep states. However, the servers cannot process the requests immediately when transiting to an active state. In this paper, a cost effective and energy efficient VM migration for scheduling in cloud computing is developed. In this technique, VMs having minimum cost and minimized energy consumption are selected for migration. During load balancing, the tasks are migrated to the underutilized server if the needed current server is overloaded. Similarly, the tasks are migrated from the under-loaded server to the current server. In energy efficient scheduling, given the arrival of user requests, the VMs are scheduled such that the total energy consumption of the data center is minimized. The proposed CEEM-VM-MS technique is implemented in Cloudusim tool. In experiments, the upper threshold value for CPU size is increased and the performance metrics power consumption, number of VM migrations, response delay, and CPU utilization are measured. Results indicate that the proposed CEEM-VM-MS technique minimizes the power consumption, reduces the number of VM migrations, reduced the response delay and increases the CPU utilization.