摘要
随着网络上多媒体数据的爆炸性增长,大量的多媒体数据在世界各地产生并共享,导致对海量可扩展存储系统的需求快速增长。在分布式网络共享环境,大量的分布式客户端同时访问服务器,对服务器的性能要求更高。针对多媒体的特点和需求,采用自治式服务器集群结构设计一种集群多媒体存储系统CMSS(Cluster Multimedia Storage System),并着重研究CMSS系统的数据组织技术,包括元数据组织、数据组织及迁移和多媒体Cache算法等。
CMSS系统设计了一种TLMS(Two-level Metadata Server)元数据组织结构。TLMS通过分离存储数据的逻辑视图与物理视图,来实现两级元数据组织结构。其中逻辑视图由全局元数据服务器GMS(Global Metadata Server)来管理,物理视图由各个存储服务器上的本地元数据服务器LMS(Local Metadata Server)来管理。采用GMS双机热备技术,既实现了单一命名空间,又避免了单点失效;利用全局元数据Cache技术,缩短了请求的处理路径,减轻了GMS的负载,从而提高了系统的性能;采用LMS技术,每个存储服务器能够自主的管理自己的存储资源和元数据及数据本身,并且能够独立提供存储服务;另外,CMSS的两级元数据组织技术避免了传统集中式元数据服务器的性能瓶颈,也解决了分布式元数据组织的元数据一致性和同步开销问题。
为了实现高性能、高扩展性,通过对传统分布式和并行数据组织的分析,设计了一种AutoData数据组织结构。AutoData采用多级数据组织结构,既具有分布式和并行数据组织的优点,又能克服两者缺点。AutoData将整个系统的存储空间分为三层:内存并行存储池、磁盘并行存储池和分布式存储池。所有存储服务器内存的一部分组成一个内存并行存储池;所有存储服务器磁盘的一小部分组成一个磁盘并行存储池;所有存储服务器的剩余磁盘存储空间组成一个分布式存储池。内存并行存储池性能最好,但是其容量最小;磁盘并行存储池性能次之,但是其容量要相对大一些;分布式存储池性能最低,但是其容量最大。
通过分析,在多个客户端同时访问服务器的情况下,虽然每个客户端访问的地址可能是顺序的,但是从存储服务器磁盘调度看来,这些多个客户端的访问地址是随机的。为了减少对磁盘的随机访问次数,设计了一种CBP(Client-Based Prefetching)预取算法,CBP算法采用基于客户端的策略,为每个客户端设置一定的预取缓存,并采用大的预取数据块,减少对磁盘的访问次数,提高了系统的性能。在Cache替换算法中,基于多媒体请求访问地址可预测的特点,设计了一种FOPT(Forecast OPT)替换算法,FOPT算法根据多媒体访问的地址连续性,来预测将来访问的地址顺序,从而实现基于预测的OPT算法。
在千兆以太网络环境下对CMSS系统进行了相应的试验测试和性能分析。在单个服务器的情况下,分别测试了CMSS和NFS的性能。总的来说,随机读情况下,CMSS服务器性能略低于NFS服务器,但是顺序读情况下,CMSS服务器性能要比NFS高20%左右。在多个服务器的并行测试环境,分别测试了CMSS、Lustre和PVFS的性能。测试结果显示,随机读情况下,CMSS服务器性能要高于Lustre,但是低于PVFS服务器,而在顺序读情况下,CMSS服务器性能要比Lustre和PVFS高30-40%。充分说明了CMSS系统针对多媒体应用顺序读优化的有效性。
仿真不同的客户端的情况下,对FOPT和LRU算法命中率进行了测试,从结果看,当请求小于64KB时,FOPT和LRU算法的命中率都很高。这个主要是因为服务器Cache采取了64KB大小的预取算法,说明了CBP算法的有效性。当请求达到64KB时,不管客户端数的多少,FOPT算法的命中率比LRU命中率高50-70%,充分说明了FOPT算法的有效性。
With the explosive growth of multimedia data on the Internet, huge amount of multimedia data have been and are continuing to be generated and shared by users around the globe. Accordingly, the demands for large scale expandable multimedia storage systems are dramatically increasing. Furthermore, multimedia date have unique demands for storage system. In a distributed network environment, a large number of clients access the servers simultaneously, putting even more rigorous performance requirement on the servers. Aiming at the traits and requirements of multimedia data, deploying an autonomous server cluster architecture, we designed a Cluster Multimedia Storage System (CMSS). More specifically, we studied the data organization algorithms including CMSS metadata management, data organization and migration, multimedia caching algorithm, etc.
CMSS emplayed a TLMS(Two-level Metadata Server) algorithm. The TLMS algorithm separates the data logical view from the physical view. The logical view is managed by a Global Metadata Server (GMS). The physical view is managed by Local Metadata Servers (LMSs) on individual storage servers. By using online fail-over technology, our GMS server implements a single name space without introducing a single point of failure. With the help of the global metadata caching technique, the request handling process is much simplified, reducing the load of the GMS server and improving the system performance. By adopting the LMS technique, each storage server can autonomously manage its private storage resources as well as metadata and actual data. In addition, each storage server can provide independent storage services. Furthermore, the CMSS two-level metadata management avoids the metadata performance bottleneck exhibited in traditional centralized metadata server solutions. It also solves the consistency and synchronization overhead problems in distributed metadata management solutions.
For the sake of combined high performance and scalability, through the analysis of traditional distributed and parallel data organization, we designed a AutoData algorithm, which utilizes a multi-level data management architecture and shares the advantage of distributed systems and parallel data organizations without bearing their deficiencies. The entire storage hierarchy consists of three layers: an in-memory parallel storage pool layer, an on-disk parallel storage pool layer and an on-disk distributed storage pool layer. The in-meory parallel storage pool is then made up of certain amount of memory from each and every of the storage server memory space. Similarly, the on-disk parallel storage pool is made up of a small amount of disk space from each and every of the server storage space. Finally, the rest of the disk storage space from the servers forms the on-disk distributed storage pool. The in-memory parallel storage pool is the smallest in size while achieving the best performance. The on-disk parallel storage pool is of relatively weaker performance and larger capacity. The on-disk distributed storage pool has the lowest performance with the largest capacity.
According to our analysis, even though the accesses from individual clients are sequential, when multiple clients access the servers at the same time, the mixed accesses from multiple clients exhibit a random access pattern. In order to reduce the number of random accesses to the disks, we designed a CBP(Client-Based Prefetching) algorithm. By reserving certain amount of buffer for prefetching and adopting large prefetching block sizes, we reduced the number of disk accesses and improved the system performance. In terms of cache replacement algorithm, based on the high predictability of multimedia accesses, we designed a forecast-based optimal cache replacement algorithm, namely Forecast OPT (FORT). We implemented the forecast-based FORT algorithm by predicting future access addresses based on the contiguity of the multimedia accesses.
We evaluated and analyzed CMSS system performance in a Gigabit Ethernet environment. We compared the single-server performances under CMSS and NFS. In general, for random reads, the CMSS server performance is slightly worse than that of the NFS server. But for sequential reads, the CMSS server performance is 20% better than NFS. In addition, we also tested the performances of CMSS, Lustre and PVFS, respectively, in a multi-server parallel storage environment. The results show that, for random reads, the CMSS server performance is better than Lustre while worse than PVFS. However, for sequential reads, the CMSS server overperforms Lustre and PVFS by 30-40%. The results reveal the effectiveness of CMSS system optimization for sequential reads.
We also compared the hit rates results under the FORT and LRU replacement algorithm by simulating a multiple-client system. The results show that the hit rate of FORT and LRU are similar and relatively high when the request sizes is below 64KB. This demonstrates the effectiveness of our algorithm by adopting the 64KB prefetching block size. When the request size reaches 64KB, regardless of the number of clients, the hit rate of the FORT algorithm is 50-70% higher than LRU, further illuminating the effectiveness of FORT algorithm.
引文
[1] G. A. Gibson, D. F. Nagle, K. Amiri, et al. File server scaling with network-attached secure disks. In Proceedings of the 1997 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. New York: ACM Press, 1997: 272~284
[2] G. A. Gibson, Rodney Van Meter. Network attached storage architecture. communications of the ACM, 2000, 43(11): 37~45
[3] Kaladhar Voruganti, Prasenjit Sarkar. An analysis of Three Gigabit Networking Protocols for Storage Area Networks. IEEE Computer, 2001, 29(4): 259~265
[4]谢长生,傅湘林,韩德志等.一种基于iSCSI的SAN的研究与实现.计算机研究与发展, 2003, 40(5): 746~751
[5] M. Factor, K. Meth, D. Naor, et al. Object Storage: The Future Building Block for Storage Systems. A position paper on Object Storage. In proceedings of the 2nd International IEEE Symposium on Mass Storage Systems and Technologies, Sardinia Italy, June 19-24, 2005: 119~123
[6] Wei Liu, Xinming Ou, Min Wu, et al. A Distributed Naming Mechanism in Scalable Cluster File System. In proceedings of the 4 th Intl Conf on High Performance Computing in Asia-Pacific Region, Vol. I, Beijing, China, 2000: 37~41
[7]谭志虎,裴先登,谢长生.附网存储—一种新的网络存储方案.电子计算机与外部设备, 1999, 23(1): 3~6
[8] Garth A. Gibson, David F. Nagle, et al. A Cost-Effective, High-Bandwidth Storage Architecture. In Proceedings of the 8th Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 1998: 92~103
[9] Nagle, D. Ganger, G. , Butler, J. et al. Network Suppport for Network-attached Storage, HotInterconnects 1999, Stanford, CA, August, 1999: 79~68
[10] R. W. Horst, D. Garcia. ServerNet SAN I/O architecture. In R. Rettberg and W. Dally, editors, Hot Interconnects Symposium V. IEEE Computer Society, 1997: 23~28
[11]李辉,谢长生,涂平.一种新型的高性能计算机存储系统的研究与实现.计算机研究与发展, 1999, 36(2): 242~250
[12] Lee, E. K. Highly-Available, Scalable Network Storage, 1995 Spring COMPCON, March, 1995. 262~268
[13] Paul Vongsathorn, Scott D. Carson. A System for Adaptive Disk Rearrangement. Software-Practice and Experience, 1990, 20(3): 225~242
[14] FU Xiang-lin, XIE Chang-Sheng, LIU Zhao-Bin. The IP based Storage of Image Information. Processing of the 2nd International Symposium on Multispectral Image Processing and Pattern Recognition. China, Oct 2001. 154~159
[15] Stephen Aiken, Dirk Grunwald, Andy Pleszkun.A Performance Analysis of the iSCSI Protocol. IEEE/NASA MSST2003 . Twentieth IEEE/Eleventh NASA Goddard Conference on Mass Storage Systems & Technologies.April, 2003, San Diego, California, USA: 135~165
[16] Wang, P. ; Gilligan, R. E. ; Green, H. ; Raubitschek, J. ; IP SAN - from iSCSI to IP-addressable Ethernet disks, Proceedings of 20th IEEE/11th NASA Goddard Conference on Mass Storage Systems and Technologies, 2003. 7-10 April 2003. 189~193
[17] Aiken, S. ; Grunwald, D. ; Pleszkun, A. R. ; Willeke, J. ; A performance analysis of the iSCSI protocol, Proceedings of 20th IEEE/11th NASA Goddard Conference on MSST, 7-10 April 2003. 123~134
[18] Simitc. H; Malakapall. C; Gunturu. V; Evaluation of SCSI over TCP/IP and SCSI over fibre channel connections, Hot Interconnects 9, 2001, 22-24 Aug, 2001. 87~91
[19] Xubin He, Qing Yang, Ming Zhang, A caching strategy to improve iSCSI performance, in Proc. of IEEE Annual Conference on Local Computer Networks, Nov. 6-8, 2002. 278~285
[20] G. A. Gibson, D. F. Nagle, K. Amiri, F. W. Chang. File Server Scaling With Network-attached Secure Disks. Performance Evaluation Review, June 1997, 25(1): 272~284
[21] SNIA-Storage Networking Industry Association. OSD: Object Based Storage Devices Technical Work Group. http: //www. snia. org/techactivities/workgroups/ osd/
[22] P. Schwan. Lustre: Building a file system for 1000-node clusters. In Proceedings of the 2003 Linux Symposium, July 2003: 1~7
[23] Panfs: Object-based architecture. http: //www. panasas. com/panfs. html
[24]黄铠,徐志伟著.可扩展并行计算—技术、结构与编程.陆鑫达等译.北京:机械工业出版社, 2000, 302~302
[25]汪东升,郑纬民.高可用集群计算.小型微型计算机系统, 2000, 21(11): 125~129
[26] H. Tang, A Gulbeden, et al. Sorrento: A Self-Organizing Storage Cluster for Parallel Data-Intensive Applications. Technical Report 2003-30, UCSB, September 2003: 1~14
[27] H. Tang, and T. Yang, An efficient data location protocol for self-managing storage clusters. In Proceedings of the 2003 ACM/IEEE conference on Supercomputing. IEEE Computer Society, 2003: 53~65
[28] Perles, A. ; Molero, X. ; Marti, A. ; Santonja, V. ; Serrano, J. J. ; Improving the execution of groups of simulations on a cluster of workstations and its application to storage area networks, In Proceedings of 34th Annual Conference on Simulation Symposium, 22-26 April 2001: 227~234
[29] Hwang K. , Jin H. , Ho, R. S. C. , Orthogonal striping and mirroring in distributed RAID for I/O-centric cluster computing . IEEE Transactions on Parallel and Distributed Systems, Jan 2002, 13(1): 26~44
[30] Wei Liu, Min Wu, Xinming Ou.Design of an I/O balancing file system on Web server clusters . In Proceedings of 2000 International Workshops on Parallel Processing, 2000: 119~125
[31] Oguchi M. Kitsuregawa M. .Data mining on PC cluster connected with storage area network: its preliminary experimental results.In Proceedings of IEEE International Conference on Communications, 7 , 2001: 2145~2149
[32] Qiang Cao, ChangSheng Xie. A self-adaptation, high availability cluster file system for network applications. In Proceedings. ICII, Beijing, 2001: 323~327
[33] Apon, A. W. , Wolinski, P. D. , and Amerson, G. M. Sensitivity of cluster file system access to I/O server selection, in Cluster Computing and the Grid 2nd IEEE/ACM International Symposium CCGRID2002, 2002: 183~192
[34] J. Kubiatowicz, D. Bindel, Y. Chen, et al. OceanStore: An architecture for global-scale persistent storage. In Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 00), ACM, 2000: 190~201
[35] S. Rhea, C. Wells, P. Eaton, et al. Maintenance-Free Global Data Storage, IEEE Internet Computing, 5(5), 2001: 40~49
[36] Roselli, D, Lorch, J. R. , Anderson, T. E. A Comparison of File System Workloads, in Proceedings Of the USENIX Annual Technical Conference. San Diego, California, June 18-23, 2000: 41~54
[37] Sandberg, R. et al. Design and Implementation of the Sun Network Filesystem, Summer USENIX, June 1985: 119~130
[38] Andy Watson, Network Appliance, Inc. Multiprotocol Data Access: NFS, CIFS, and HTTP TR3014 Network Appliance, Mountain view, California, March 1995: 154~260
[39] Hitz, D. , Lau, J. and Malcolm, M. File Systems Design for an NFS File Server Appliance, Winter USENIX, January 1994: 120~126
[40] J. Postel and J. Reynolds, File Transfer Protocol (FTP), RFC 959, ISI, Oct 1985: 68~74
[41] Russell, M. T. And Hopkins, T. R. CFTP -- A Caching FTP Server, Computer Networks and ISDN Systems, Presented at the 3rd International Caching Workshop, Manchester, 15th-17th June 1998. August 1998, 30(22): 2211~2222
[42] S. Rhea, C. Wells, P. Eaton, D. Geels, B. Zhao, H. Weatherspoon, and J. Kubiatowicz, Maintenance-Free Global Data Storage, IEEE Internet Computing, 2001, 5(5): 40~49
[43] Bin Jia; Mei-Hwa Chen; Maniatty, W. ; Server directed file domain allocation for noncontiguous file access Cluster Computing and the Grid, 2004. CCGrid 2004. IEEE International Symposium on , April 2004: 19~22
[44] Frank Schmuck and Roger Haskin:GPFS: A Shared-Disk File System for Large Computing Clusters, Proceedings of the Conference on File and Storage Technologies (FAST’02), 28–30 January 2002, Monterey, CA, 2002: 231~244 (USENIX, Berkeley, CA. )
[45] L. Cabrera and D. Long, Swift: Using distributed disk striping to provide high I/O data rates. ACM Computing Systems, 4, 1991: 405~436
[46] P. Yianilos and S. Sobti. The evolving field of distributed storage. IEEE Internet Computing, 2001, 5(5): 35~39
[47] J. Kubiatowicz, D. Bindel, Y. Chen, OceanStore: An architecture for global-scalepersistent storage. In Proceedings of ACM ASPLOS, November 2000: 190~201
[48] Lin-wen lee, P. Scheuermann,“File Assignment in Parallel I/O Systems with Minimal Variance of Service Time”, IEEE computer, Feb. , 2000, 49(2): 127~140
[49] P. H. Carns, W. B. Ligon, R. B. Ross, R. Thakur. PVFS: A Parallel File System for Linux Clusters. In Proceedings of the 4th Annual Linux Showcase and Conference, Atlanta, GA, 2000: 317~327
[50] Murali Vilayannur, Ross, R. B. , Carns P. H. et al. On the performance of the POSIX I/O interface to PVFS. In Proceedings of Parallel, Distributed and Network-Based Processing, 2004. 12th Euromicro Conference, 11-13 Feb. 2004: 332~339
[51] Sharad Garg, Jens Mache: Performance Evaluation of Parallel File Systems for PC Clusters and ASCI Red. In Proceedings of the 2001 IEEE International Conference on Cluster Computing (CLUSTER. 01) , 2001: 172~183
[52] Y. Zhu, H. Jiang, X. Qin, et al. Scheduling for Improved Write Performance in a Cost-Effective, Fault-Tolerant Parallel Virtual File System (CEFT-PVFS), In Proceedings of the 4th LCI International Conference on Linux Clusters: The HPC Revolution 2003, June 24-26, 2003, San Jose, California.
[53] Y. Zhu, H. Jiang, X. Qin, et al. Improved Read Performance in a Cost-Effective, Fault-Tolerant Parallel Virtual File System (CEFT-PVFS), In Proceedings of IEEE/ACM Cluster Computing and Computational Grids (CCGRID), May 2003, Japan. 2003: 730~735
[54] Lior Amar, Amnon Barak, Amnon Shiloh, The MOSIX Parallel I/O System for Scalable I/O Performance, In Proceedings of 14-th IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS 2002)
[55] Garcia-Carballeira, F. Carretero, J. Calderon, A. et al. An adaptive cache coherence protocol specification for parallel input/output systems. IEEE Transactions on Parallel and Distributed Systems, June 2004, 15(6): 533~545
[56] Perez, M. S. Sanchez, A. Robles, V. et al. Cooperation model of a multiagent parallel file system for clusters. In Proceedings of Cluster Computing and the Grid, 2004. CCGrid 2004. 19-22 April 2004: 595~601
[57] Xiaohui Shen, Alok Choudhary, DPFS: A Distributed Parallel File System, In Proceedings of the 2001 International Conference on Parallel Processing (ICPP’01) , Valencia, Spain, 2001: 1~15
[58] W. Bolosky, J. Douceur, D. Ely, et al. Feasibility of a serverless distributed file system deployed on an existing set of desktop PCs. In ACM SIGMETRICS Conference, June 2000
[59] T. Anderson, M. Dahlin, J. Neefe, et al. Server-less Network File Systems, ACM Trans. on Computer Systems, Jan. 1996: 41~79
[60] J. H. Hartman and J. K. Ousterhout, The Zebra Striped Network File System. ACM Transactions on Computer Systems, 1995, 13(3): 279~310
[61] Roger L. Haskin and Frank B. Schmuck. The Tiger Shark File System, In Proceedings of COMPCON’96. 1996: 226~231
[62] F. Fabbrocino, J. R. Santos? and R. Muntz, An Implicitly Scalable, Fully Interactive Multimedia Storage Server, In Proceedings of the 2nd International Workshop on Distributed Interactive Simulation and Real-Time Applications, 1998: 92~101
[63] R. D. Hersch. Parallel storage and retrieval of pixmap images. In Proceedings of the 12th IEEE Symposium on Mass Storage System, Monterey, 1993: 221~226
[64] GigaView: Comparing Multimedia Storage Architectures: Proc. Int'l Conf. on Multimedia Computing and Systems IEEE Press, Washington, USA, 1995: 323~329
[65] C. K. Wong. Minimizing Expected Head Movement in One-Dimensional and Two-Dimensional Mass Storage Systems. Computing Surveys, 1980, 12(2): 167~178
[66] D. James Gemmell and Jiawei Han. Multimedia Network File Servers: Multi-Channel Delay Sensitive Data Retrieval. Multimedia Systems, 1994, 1(6): 240~252
[67] J. R. Snatos and R. Muntz, Performance Analysis of the RIO Multimedia Storage System with Heterogeneous Disk Configurations, In Proceedings of 6th ACM International Multimedia Conference, 1998
[68] P. Venkat Rangan and Harrick M. Vin. Efficient Storage Techniques for Digital Continuous Multimedia. IEEE Transaction on Knowledge and Data Engineering, August 1993. 5(4): 564~573
[69] A. L. Narasimha Reddy and J. Wyllie. I/O Issues in a Multimedia System. COMPUTER, 1994. 27(3): 69~74
[70] P. J. Shenoy, P. Goyal, S. S. Rao, and H. M. Vin, Symphony: An Integrated Multimedia File System, Proceedings of SPIE/ACM Conference on Multimedia Computing and Networking, 1998: 124~138
[71] William J. Bolosky, Robert P. Fitzgerald, John R. Douceur. Distributed Schedule Management in the Tiger Video Fileserver, In Proceedings of SOSP-16, St. -Malo, France, Oct. 1997: 212~223
[72] Gemmell, H. M. Vin, D. D. Kandlur, P. V. Rangan, and L. A. Rowe, Multimedia Storage Servers: A Tutorial, IEEE Computer, May 1995, 28(5): 40~49
[73] A. Heybey, M. Sullivan, and P. England, Calliope: A distributed, scalable multimedia server, In Proceedings of USENIX 1996 Annual Technical Conference, 1996
[74] C. Akinlar and S. Mukherjee. A Scalable Distributed Multimedia File System Using Network Attached Autonomous Disks. In Proceedings of 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, 2000: 180~187
[75] VoDKA Projects. http: // http: //vodka. lfcia. org/
[76] Alice Bonhomme and Loic Prylli, A Distributed Storage System for a Video-on-Demand Server, Lecture Notes in Computer Science, 2001, 1900: 1100~1110
[77] Cyrus Shahabi, Roger Zimmermann, Kun Fu, and Shu-Yuen Didi Yao. Yima: a second-generation continuous media server, Computer, , June 2002, 35(6): 56~62
[78] Roger. Zimmermann, Kun Fu, Cyrus Shahabi, Didi Yao and Hong Zhu, Yima: Design and Evaluation of a Streaming Media System for Residential Broadband Services, In Proceedings of VLDB 2001 Workshop Databases in Telecommunications, Springer-Verlag, Berlin, 2001: 116~125
[79] A. Calvagna, A. Puliafito and L. Vita. Design and implementation of a low-cost/ high-performance Video on Demand server, Microprocessors and Microsystems. 24, 2000: 299~305
[80] C. K. Chang, C. C. Shih, T. T. Nguyen and P. Mongkolwat, A Popularity-based Data Allocation Scheme for a Cluster-based VOD Server, In Proceedings of COMPSAC'96, Seoul, Korea, August 1996: 62~67
[81] W. J. Bolosky, Robert P. Fitzgerald et al, Distributed Schedule Management in the Tiger Video Fileserver, In Proceedings of of SOSP-16[C]. 1997: 212~223
[82] Milind Buddhikot and Gurudatta, Parulkar, Efficient Data Layout, Scheduling and Playout Control in MARS, In Proceedings of the 5th International Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV),April 1995
[83] D. H. C. Du and Y. J. Lee, Scalable server and storage architectures for video streaming, In Proceedings of IEEE Int. Conf. Multimedia Computing and Systems, June 1999: 62~67
[84] J. Gafsi and E. Biersack, A Novel Replication Placement Strategy for Video Servers, 6th International Workshop on Interactive and Distributed Multimedia Systems, Toulouse, France, October,1999 : 12~15
[85] W. Tetzlaff and R. Flynn, Disk Striping and Block Replication Algorithm for Video File Servers, In Proceedings of ICMCS’96, June 1996: 590~597
[86] N. Venkatasubramanian and S. Ramanthan, Load Management in Distributed Video Servers, In Proceedings of 17th Int’I Conf. On Distributed Computing Systems, IEEE Computer Society Press, Los Alamitos, Calif. , 1997: 528~535
[87]彭宇行,陈福接.分布式VoD系统的视频数据存储,计算机学报, 2000. 23(6): 271~273
[88] A Dan , D Sitaram. and , R Mukherjee, Buffering and Caching in Large-Scale Video Servers[C]. In Proceedings of IEEE CompCon, 1995: 217~224
[89] A Dan, D Sitaram. A Generalized Interval Caching Policy for Mixed Interactive and Long Video Enviroments[C]. In Proceedings of Multimedia Computing and Networking Conference, San Jose, CA, 1996: 1
[90] B Ozden, R Rastogi, A Silberschats. Buffer Replacement Algorithm for Multimedia Storage Systems. In: Proc International Conf on Multimedia Computing and Systems, Hiroshima, Japan, 1996: 580~589
[91] M Dahlin, R Wang, T Anderson et al. Cooperative Caching: Using Remote Client Memory to Improve File System Performance[C]. In Proceedings of the First Symp on Operating Systems Design and Implementation, 1994,11: 267~280
[92] D L Eager, M C Ferris, M K Vernon. Optimized regional caching in heterogeneous systems. Mathematical Programming Technical Report 98-15, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, 1998
[93]刘宇杰,秦肖臻,彭力等.一种基于P2P的视频点播系统设计,计算机技术与发展, 2007. 1, 17(1): 193~198
[94] Sung Bae Jun, Won Suk Lee, Video Allocation Methods in a Multi-level Server forLatge-scale VOD Services, IEEE Transactions on Consumer Electronics, November 1998, 44(4): 1309~1318
[95] Shueng-Han Gary Chan, Fouad A. Tobagi, Hierarchical Storage Systems for On Demand Video Servers, Proceedings of the SPIE, Vol. 2604, 1996: 103~120
[96]徐渐,舒继武,温冬婵.基于SAN的虚拟化系统元数据组织策略,清华大学学报, 2006, 46(7): 1289~1292
[97] Shahram Ghandeharizadeh, Cyrus Shahabi, On Multimedia Repositories, Personal Computers, and Hierarchical Storage Systems, ACM Multimedia, San Francisco, California, October 1994: 407~416
[98] Kian Lee Tan, Beng Chin Ooi, Tat Seng Chua, On Video-On-Demand Servers with Hierarchical Storage, The 5th International Conference on Database Systems for Advanced Applications, Melbourne, Australia, April 1997: 491~500
[99] Peter Triantafillou, Thomas Papadakis, On-Demand Data Elevation in a Hierarchical Multimedia Storage Server, The 23th International Conference on Very Large Data Bases, Athens, Greece, August 1997: 226~235
[100] J. Wilkes, R. Golding, C. Staelin et al. The HP AutoRAID hierarchical storage system. ACM Transactions on Computer Systems, 1996, 14(1): 108~136
[101] X. Shen, A. Choudhary, C. Matarazzo, et al. A Distributed Multi-Storage Resource Architecture and 1/O Performance Prediction for Scientific Computing, Cluster Computing 6, 2003: 189~200
[102] Siu-Wah Lau, John C. S. Lui, Designing a Hierarchical Multimedia Storage Server, The Computer Journal, November 1997. 40(9): 529~540
[103] E. Varki, S. X. Wang, A Performance Model of Disk Array Storage Systems, The Computer Measurement Group's 2000 International Conference, Orlando, Florida, December 2000: 635~644