MapReduce has become a popular framework for big data applications. While MapReduce has received much praise for its scalability and efficiency, it has not been thoroughly evaluated for power consumption. In this paper, the authors explore the possibility of scheduling in a power-efficient manner without the need for expensive power monitors on every node. They begin by considering that no cluster is truly homogeneous with respect to energy consumption. From there they develop a MapReduce framework that can evaluate the current status of each node and dynamically react to estimated power usage.