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Massive Storage Systems

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Abstract

To accommodate the explosively increasing amount of data in many areas such as scientific computing and e-Business, physical storage devices and control components have been separated from traditional computing systems to become a scalable, intelligent storage subsystem that, when appropriately designed, should provide transparent storage interface, effective data allocation, flexible and efficient storage management, and other impressive features. The design goals and desirable features of such a storage subsystem include high performance, high scalability, high availability, high reliability and high security. Extensive research has been conducted in this field by researchers all over the world, yet many issues still remain open and challenging. This paper studies five different online massive storage systems and one offline storage system that we have developed with the research grant support from China. The storage pool with multiple network-attached RAIDs avoids expensive store-and-forward data copying between the server and storage system, improving data transfer rate by a factor of 2–3 over a traditional disk array. Two types of high performance distributed storage systems for local-area network storage are introduced in the paper. One of them is the Virtual Interface Storage Architecture (VISA) where VI as a communication protocol replaces the TCP/IP protocol in the system. VISA’s performance is shown to achieve better than that of IP SAN by designing and implementing the vSCSI (VI-attached SCSI) protocol to support SCSI commands in the VI network. The other is a fault-tolerant parallel virtual file system that is designed and implemented to provide high I/O performance and high reliability. A global distributed storage system for wide-area network storage is discussed in detail in the paper, where a Storage Service Provider is added to provide storage service and plays the role of user agent for the storage system. Object based Storage Systems not only store data but also adopt the attributes and methods of objects that encapsulate the data. The adaptive policy triggering mechanism (APTM), which borrows proven machine learning techniques to improve the scalability of object storage systems, is the embodiment of the idea about smart storage device and facilitates the self-management of massive storage systems. A typical offline massive storage system is used to backup data or store documents, for which the tape virtualization technology is discussed. Finally, a domain-based storage management framework for different types of storage systems is presented in the paper.

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Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, P.R. China

    Dan Feng & Hai Jin

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  1. Dan Feng
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  2. Hai Jin
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Correspondence to Dan Feng.

Additional information

Survey: This paper is supported by the National Natural Science Foundation of China under Grants No.60125208, No.60273074, No.60303032, No.69973017, and the National Grand Fundamental Research 973 Program of China under Grants No.2004CB318201, No. 2003CB317003.

Dan Feng received the Ph.D. degree from Huazhong University of Science and Technology (HUST), Wuhan, China, in 1997. She is currently a professor of School of Computer, HUST. Her research interests include computer architecture, storage system, parallel I/O, massive storage and performance evaluation.

Hai Jin received his Ph.D. degree in computer engineering from HUST in 1994. Dr. Jin now is a professor of computer science and engineering, the director of Cluster and Grid Computing Lab, and the Dean of School of Computer Science and Technology at HUST. He also is the chief scientist of the ChinaGrid project, one of the largest national grid computing in China. His research interests include computer architecture, cluster computing, grid computing, semantic web, peer-to-peer computing, network storage, network security, and pervasive computing.

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Feng, D., Jin, H. Massive Storage Systems. J Comput Sci Technol 21, 648–664 (2006). https://doi.org/10.1007/s11390-006-0648-x

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