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    Liao Bin, Yu Jiong, Sun Hua, Nian Mei. Energy-Efficient Algorithms for Distributed Storage System Based on Data Storage Structure Reconfiguration[J]. Journal of Computer Research and Development, 2013, 50(1): 3-18.
    Citation: Liao Bin, Yu Jiong, Sun Hua, Nian Mei. Energy-Efficient Algorithms for Distributed Storage System Based on Data Storage Structure Reconfiguration[J]. Journal of Computer Research and Development, 2013, 50(1): 3-18.

    Energy-Efficient Algorithms for Distributed Storage System Based on Data Storage Structure Reconfiguration

    • As an underlying core infrastructure and important component of cloud computing, distributed storage system is the foundation of all kinds of cloud services or applications. However, with the expanding of system scale and energy consumption factors being ignored by its designers, the problem of high energy consumption is exposed. Because of data availability requirements, we cannot simply use the existing energy-saving technologies to solve the distributed storage system’s high energy consumption problem. To ensure all data’s availability is the premise of designing energy-efficient algorithms for distributed storage system. In this paper, we create a system and data availability model. After studying the storage structure and mechanism, the relationship between server’s status and data’s availability, the method to solve the problem of full covering by constructing a data’s availability measurement matrix is proposed. The energy saving model for distributed storage system is defined. The RACK is divided into Active-Zone and Sleep-Zone distinct storage area. According to the different data access frequency and regularity, we calculate the different activity factors for different data which decide how many replicas are stored in Active-Zone. The servers in Sleep-Zone are turn to sleep for energy saving while the work load of data center is low. Experimental results show that, the energy-efficient algorithms in this paper adapt the access rule and the availability of all the data in system, improve the energy-efficient of distributed storage system, and the algorithm is more efficient when the system’s work load and average activity factor is low.
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