Title :
Designing a Power-Aware Replication Strategy for Storage Clusters
Author :
Lingwei Zhang ; Yuhui Deng
Author_Institution :
Dept. of Comput. Sci., Jinan Univ., Guangzhou, China
Abstract :
The exponential data growth is presenting challenges to traditional storage systems. Component-based cluster storage systems, due to their high scalability, are becoming the architecture of next generation storage systems. Cluster storage systems often use data replication to ensure high availability, fault tolerance, and load balance. However, this kind of data replication not only consumes a large amount of storage resources, but also generates more energy consumption. This paper presents a power-aware data replication strategy by leveraging data access behavior. This strategy uses 80/20 rule (80% of the data accesses often go to 20% of the storage space) to replicate only a small amount of frequently accessed data. Furthermore, the storage nodes are divided into a hot node set and a cold node set. Hot nodes, which store a small amount of hot data copies, are always in an active state to guarantee the QoS of the system. The cold nodes which store a large number of infrequently accessed cold data, are placed in a low power state, thus reducing the energy consumption of the cluster storage system. The experimental results show that the proposed strategy can effectively reduce the resource and energy consumption of the system, while ensuring the system performance.
Keywords :
energy consumption; object-oriented programming; pattern clustering; power aware computing; quality of service; storage management; QoS; cold data; cold node; component-based cluster storage systems; data access behavior; energy consumption; exponential data growth; fault tolerance; hot data copy; hot node; load balance; low power state; next generation storage systems; power-aware data replication strategy; power-aware replication strategy; storage clusters; storage nodes; storage resources; storage space; system performance; Availability; Heating; Power demand; Servers; Switches; Time factors; data replication; energy consumption; hotspot data; storage cluster;
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.57