HotSpot & Cache:An Optimization Method for Small Objects Storage in SWIFT of OpenStack Cloud
In the big-data era,cloud platforms such as OpenStack aim at the optimization of storage performance for large objects.However small file severely hurdles its performance.In this paper,a framework,namely HotSpot & Cache,is proposed to optimize the storage performance for small objects in SWIFT of OpenStack cloud.Double-proxy architecture is adopted for HotSpot & Cache architecture,including an external proxy node,an internal proxy node,and a dedicated cache server.Storage performance optimization for small objects is accomplished in the unit of partitions in storage nodes,hot-spot partitions are predicted and cached in the dedicated cache server.A series of facilities are implemented for small objects storage performance optimization,e.g.Sampling & Statistics,Hot-Spot Prediction,and a Request Redirection.The access frequency and the size of a partition is periodically sampled and statistically accumulated to predict the hot-spot of a partition for the next interval.Experimental results demonstrate the effectiveness of the proposed HotSpot & Cache architecture.
Cloud computing small files performance optimization SWIFT
Xueming Qiao Xue Han Dongjie Zhu Yuan Zhang Haifeng Sun Mingli Yin Xiangkun Zhang
State Grid Shangdong Electric Power Company,WeiHai Power Supply Company Heihe University School of Computer Science and Technology,Harbin Institute of Technology,Weihai
国际会议
西安
英文
7-12
2018-09-21（万方平台首次上网日期，不代表论文的发表时间）