In this paper, we present a thermal-aware file assignment technique called TIGER for reducing the cooling cost of storage clusters in data centers. We show that peak inlet temperatures of storage nodes depend on not only CPU utilization but also I/O activities, which rely on file assignments in a cluster. The TIGER scheme aims to lower peak inlet temperatures of storage clusters by dynamic thermal management through file placements. TIGER makes use of cross-interference coefficients to estimate the re-circulation of hot air from the outlets to the inlets of data nodes. TIGER first calculates the thresholds of disks in each data node based on its contribution to heat re-circulation in a data center. TIGER undertakes two steps to achieve high I/O performance while reducing cooling cost. First, TIGER assigns groups of files with similar service times to shorten I/O response times. Second, TIGER ensures that load imbalance does not exceed a specified threshold. We evaluate performance of TIGER in terms of both cooling energy conservation and response time of a storage cluster. Our results confirm that TIGER reduces cooling-power requirements for clusters by offering about 10 to 15 percent cooling-energy savings without significantly degrading I/O performance.

In this paper, we present thermal-aware file assignment technique called TIGER for reducing cooling cost of storage clusters in data centers. TIGER first calculates the thresholds of disks in each node based on its contribution to heat recirculation in a data center. Next, TIGER assigns files to data nodes according to calculated thresholds. We evaluated performance of TIGER in terms of both cooling energy conservation and response time of a storage cluster. Our results confirm that TIGER reduces cooling-power requirements for clusters by offering about 10 to 15 percent cooling energy savings without significantly degrading I/O performance.