Datacenters are facilities used to house computer systems. These facilities generally consume a large amount of energy. In recent years, many researches proposed datacenter management frameworks that allow energy to be utilized more efficiently. However, most of these frameworks were limited by constraints related to unpredictable behaviors of applications in both the perspectives of execution time and power consumption. In order to provide an efficient task scheduling in datacenters, this paper proposes a preliminary concept called a robust energy-efficient framework. In this framework, a software system is deployed on top of a datacenter middleware to oversee process migrations among heterogeneous machines with various configurations. Moreover, the framework integrates additional subsystems for tracking behavioral changes of scheduled processes. During runtime, these subsystems periodically generate profiles from monitored performance metrics of processes and machines. Process profiles represent resource-usage behavior of an application, while machine profiles represent resource-provisioning behaviors. Processes can be moved around on the fly based on information provided in these profiles. The proposed framework takes advantage of heterogeneity along with process migration to improve energy efficiency of a datacenter without prior knowledge on process behavior and resource usage fluctuation in users’ applications.