A Data-Mining-Based Prefetching Approach to Caching for Network Storage Systems

  • Authors:

  • Xiao Fang;Olivia R. Liu Sheng;Wei Gao;Balakrishna R. Iyer

  • Affiliations:

  • Department of Information, Operations and Technology Management, University of Toledo, Toledo, Ohio 43606, USA;School of Accounting and Information Systems, University of Utah, Salt Lake City, Utah 84112, USA;Department of Information and Communication Systems, Schools of Business Administration, Fordham University, New York, New York 10023, USA;IBM Silicon Valley Lab, San Jose, California 95141, USA

  • Venue:
  • INFORMS Journal on Computing
  • Year:
  • 2006

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Abstract

The need for network storage has been increasing rapidly owing to the widespread use of the Internet in organizations and the shortage of local storage space due to the increasing size of applications and databases. Proliferation of network storage systems entails a significant increase in the number of storage objects (e.g., files) stored, the number of concurrent clients, and the size and number of storage objects transferred between the systems and their clients. Performance (e.g., client-perceived latency) of these systems becomes a major concern. Previous research has explored techniques for scaling up the number of storage servers involved to enhance the performance of network storage systems. However, adding servers to improve system performance is an expensive solution. Moreover, for a WAN-based network storage system, the bottleneck for its performance improvement typically is not caused by the load of storage servers, but by the network traffic between clients and storage servers. This paper introduces an Internet-based network storage system named NetShark and proposes a caching-based performance-enhancement solution for such a system. The proposed performance-enhancement solution is validated using a simulation.