Cloud computing is an emerging technology which is rapidly being adopted by industries, government and academia. However, the power consumption of the underlying data center has a critical impact for its known impact on the environment and the Cloud electricity bills. Therefore, there is a need for scheduling framework in the Cloud which takes into account the optimization of the power consumption of the Cloud. In this paper, we propose an Energy-Aware Task Scheduling (EATS) cloud computing framework which is responsible to schedule users' tasks considering the energy consumption when running those tasks. This paper describes our framework, and report on workload classifications of energy consumption. The results reveal that CPU-bound applications are the most consumer of energy, and therefore should be accounted for in any framework of energy-efficient scheduling, and that strategies based on shutdowns and startups should be avoided.