Title :
Stable Set Model Based Methods for Large-capacity Client Cache Management
Author :
Guo, Mingyang ; Liu, Liu ; Zhang, Yongle ; Liu, Zhenjun ; Xu, Lu
Author_Institution :
Inst. of Comput. Technol., Beijing, China
Abstract :
The performance and scalability of centralized network storage systems cannot follow the processing needs of rapid growing data. Using large-capacity client caches is one of the solutions. This paper points out that the efficiency of “data exchange” between phases is the most important problem in managing large-capacity cache. And then, it defines Stable Set Model (SSM), which can characterize the phase-transition behaviour of a data access stream, and obtain granularity selection and two localities, so as to increase the efficiency of client caches in “data exchange”. Using SSM based methods can optimize the backend load and response time of network storage systems. Experimental results show that they can decrease backend load to 2.0%~15.8% and total response time to 0.8%~15.2% compared with traditional ones when cache capacity is large.
Keywords :
cache storage; client-server systems; information retrieval; set theory; storage area networks; SSM-based methods; backend load optimization; cache capacity; centralized network storage systems; data access stream; data exchange efficiency; granularity selection; large-capacity client cache management; phase-transition behaviour; response time; scalability; stable set model based methods; Data models; Predictive models; Scalability; Servers; Silicon; Throughput; Time factors; cache granularity; client cache; locality characterizing; network storage; phase-transition behavior; pre-fetch; replacement;
Conference_Titel :
High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on
Conference_Location :
Liverpool
Print_ISBN :
978-1-4673-2164-8
DOI :
10.1109/HPCC.2012.97