TY - GEN
T1 - Hybrid storage throughput allocation among multiple clients in heterogeneous data center
AU - Huo, Zhisheng
AU - Xiao, Limin
AU - Zhong, Qiaoling
AU - Li, Shupan
AU - Li, Ang
AU - Ruan, Li
AU - Liu, Kelong
AU - Zang, Yuanyuan
AU - Wang, Pei
AU - Lu, Zheqi
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/23
Y1 - 2015/11/23
N2 - The SSD is adopted to improve the IO performanceof the storage system in the data center, the throughput allocation for clients is a challenging problem. We need to find a throughput allocation method, which can determine the throughput allocations of clients on each server, while both providing the fair allocations for clients and maximizing the utilization of system throughput resource in the entire data center. In this paper, we propose an unified allocation framework(UAF), UAF jointly allocates throughput resource across allheterogeneous storage servers, can achieve the fair throughput allocations for all clients and maximize the utilization of system throughput resource in the entire data center. We can prove that UAF satisfies fairness properties of Envy Freedom, Sharing Incentive and Pareto Optimality. We evaluated the performance of UAF using both simulation and implementation in a cluster consisting of multiple heterogeneous storage severs. The experiment results show our method can determine the throughput allocations of clients in each server, and provide both the efficient and fair allocation in the entire data center.
AB - The SSD is adopted to improve the IO performanceof the storage system in the data center, the throughput allocation for clients is a challenging problem. We need to find a throughput allocation method, which can determine the throughput allocations of clients on each server, while both providing the fair allocations for clients and maximizing the utilization of system throughput resource in the entire data center. In this paper, we propose an unified allocation framework(UAF), UAF jointly allocates throughput resource across allheterogeneous storage servers, can achieve the fair throughput allocations for all clients and maximize the utilization of system throughput resource in the entire data center. We can prove that UAF satisfies fairness properties of Envy Freedom, Sharing Incentive and Pareto Optimality. We evaluated the performance of UAF using both simulation and implementation in a cluster consisting of multiple heterogeneous storage severs. The experiment results show our method can determine the throughput allocations of clients in each server, and provide both the efficient and fair allocation in the entire data center.
KW - Efficiency
KW - Fairness
KW - Heterogeneous data center
KW - Hybrid storage
KW - Throughput allocation on each server
UR - https://www.scopus.com/pages/publications/84961725681
U2 - 10.1109/HPCC-CSS-ICESS.2015.49
DO - 10.1109/HPCC-CSS-ICESS.2015.49
M3 - 会议稿件
AN - SCOPUS:84961725681
T3 - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
SP - 140
EP - 147
BT - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015
Y2 - 24 August 2015 through 26 August 2015
ER -