摘要
Network storage provides high scalability, availability and flexibility for storage systems, and is widely applied to many fields. Particularly, I/O performance is of great significance. Its application is wide and expanding rapidly. I/O performance has already become the bottleneck of the whole performance of computer systems for a long time, and under the condition of the present computer technology, I/O performance optimization method looks especially important. In the paper, I/O performance model was analyzed based on the combination of quasi birth, death process and queuing model, and then solved the model. A number of important related performance indicators and the relationship between them were given. By the way of example, this method can show the I/O performance more accurately. Finally, we got some useful conclusions, which may be used to evaluate network storage performance, and are the basis of confirming I/O scheduling strategy.
Network storage provides high scalability, availability and flexibility for storage systems, and is widely applied to many fields. Particularly, I/O performance is of great significance. Its application is wide and expanding rapidly. I/O performance has already become the bottleneck of the whole performance of computer systems for a long time, and under the condition of the present computer technology, I/O performance optimization method looks especially important. In the paper, I/O performance model was analyzed based on the combination of quasi birth, death process and queuing model, and then solved the model. A number of important related performance indicators and the relationship between them were given. By the way of example, this method can show the I/O performance more accurately. Finally, we got some useful conclusions, which may be used to evaluate network storage performance, and are the basis of confirming I/O scheduling strategy.
基金
Sponsored by the National Natural Science Foundation of China(Grant No. 61073047)
the Fundamental Research Funds for the Central Universities(Grant No.HEUCFT1007andHEUCF100607)
the State Key Laboratory of High-End Server & Storage Technology(Grant No.2009HSSA08)
