Abstract-Cluster storage systems are essential building blocks for many high-end computing infrastructures. Although energy conservation techniques have been intensively studied in the context of clusters and disk arrays, improving energy efficiency of cluster storage systems remains an open issue. To address this problem, we describe in this paper an approach to implementing an energyefficient cluster storage system or ECOS for short. ECOS relies on the architecture of cluster storage systems in which each I/O node manages multiple disks -one buffer disk and several data disks. Given an I/O node, the key idea behind ECOS is to redirect disk requests from data disks to the buffer disk. To balance I/O load among I/O nodes, ECOS might redirect requests from one I/O node into the others. Redirecting requests is a driving force of energy saving, and the reason is two-fold. First, ECOS makes an effort to keep buffer disks active while placing data disks into standby in a long time period to conserve energy. Second, ECOS reduces the number of disk spin downs/ups in I/O nodes. The idea of ECOS was implemented in a Linux cluster, where each I/O node contains one buffer disk and two data disks. Experimental results show that ECOS improves the energy efficiency of traditional cluster storage systems where buffer disks are not employed. Adding one extra buffer disk into each I/O node seemingly has negative impact on energy saving. Interestingly, our results indicate that ECOS equipped with extra buffer disks is more energy efficient than the same cluster storage system without the buffer disks. The implication of the experiments is that using existing data disks in I/O nodes to perform as buffer disks can achieve even higher energy efficiency.
In REF , the authors proposed an architecture of cluster storage systems, in which each I/O node manages multiple disks -one buffer disk and several data disks.
ECOS: An energy-efficient cluster storage system
2009 IEEE 28th International Performance Computing and Communications Conference
2009 IEEE 28th International Performance Computing and Communications Conference
Computer Science