TY - GEN
T1 - A Load-Balancing Data Caching Scheme in Multi-tiered Storage Systems
AU - Chang, Hsung Pin
AU - Luo, Jhih Cheng
AU - Chang, Da Wei
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/1/20
Y1 - 2017/1/20
N2 - Recently, the multi-tiered storage systems that are composed of hard disk drives (HDDs) and solid state disk drives (SSDs) have received significant attention. The multi-tiered storage system extends the storage hierarchy by using SSDs to cache data from the HDDs. Thus, how to cache the appropriate data on the SSDs becomes an important issue for the multi-tiered storage systems. Due to the tremendous superior access performance of SSDs, current data caching schemes tried to cache the hottest data in SSDs, expecting that all of the disk I/O requests can be served by the SSDs. However, when the disk I/O load is heavy, such a scheme would saturate the bandwidths of SSDs and cause a negative impact on the I/O performance. To address this issue, on the basis of Profit Caching, this paper proposes a new data caching scheme, called Load-Balancing Caching Scheme (LBSC), for multi-tiered storage systems. LBSC takes the instant load of different storage devices for making the caching decision. Specifically, LBSC balance the load of SSDs and HDDs so as to fully exploit both the potential bandwidths of the SSDs and HDDs. We have implemented our scheme in a DiskSim-based multi-tiered storage simulator. From the experimental results, our proposed LBSC data caching scheme can significantly enhance the I/O performance of Profit Caching.
AB - Recently, the multi-tiered storage systems that are composed of hard disk drives (HDDs) and solid state disk drives (SSDs) have received significant attention. The multi-tiered storage system extends the storage hierarchy by using SSDs to cache data from the HDDs. Thus, how to cache the appropriate data on the SSDs becomes an important issue for the multi-tiered storage systems. Due to the tremendous superior access performance of SSDs, current data caching schemes tried to cache the hottest data in SSDs, expecting that all of the disk I/O requests can be served by the SSDs. However, when the disk I/O load is heavy, such a scheme would saturate the bandwidths of SSDs and cause a negative impact on the I/O performance. To address this issue, on the basis of Profit Caching, this paper proposes a new data caching scheme, called Load-Balancing Caching Scheme (LBSC), for multi-tiered storage systems. LBSC takes the instant load of different storage devices for making the caching decision. Specifically, LBSC balance the load of SSDs and HDDs so as to fully exploit both the potential bandwidths of the SSDs and HDDs. We have implemented our scheme in a DiskSim-based multi-tiered storage simulator. From the experimental results, our proposed LBSC data caching scheme can significantly enhance the I/O performance of Profit Caching.
UR - http://www.scopus.com/inward/record.url?scp=85013677918&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85013677918&partnerID=8YFLogxK
U2 - 10.1109/HPCC-SmartCity-DSS.2016.0028
DO - 10.1109/HPCC-SmartCity-DSS.2016.0028
M3 - Conference contribution
AN - SCOPUS:85013677918
T3 - Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
SP - 124
EP - 127
BT - Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
A2 - Yang, Laurence T.
A2 - Chen, Jinjun
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
Y2 - 12 December 2016 through 14 December 2016
ER -