With the rise of the cloud computing, saving energy consumed by cloud systems has become a tricky issue nowadays. How to place data efficiently and schedule the nodes effectively in a cloud platform are very important issues from the view of the energy-saving. However, the state-of-the-art node-scheduling strategies can't save large amount of energy for the cloud computing platforms significantly. This paper proposes a heuristic data placement algorithm and two node scheduling strategies for

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... ud platforms to save energy with tasks guaranteed. The Cloudsim is employed to simulate a private cloud system. Energy-saving is achieved by turning on minimum nodes to cover maximum data blocks. The problem of covering data block with computing nodes is abstracted as a set cover problem, and a greedy algorithm is utilized to solve this problem. This approach is practical to any cloud computing infrastructure. The designed experiment verifies the efficiency of the data placement algorithm and node scheduling strategies proposed in this paper.