MHS: A distributed metadata management strategy

  • Authors:
  • Juan Wang;Dan Feng;Fang Wang;Chengtao Lu

  • Affiliations:
  • Key Laboratory of Data Storage System, Ministry of Education, School of Computer, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China;Key Laboratory of Data Storage System, Ministry of Education, School of Computer, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China;Key Laboratory of Data Storage System, Ministry of Education, School of Computer, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China;Key Laboratory of Data Storage System, Ministry of Education, School of Computer, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2009

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Abstract

This paper proposes a novel distributed metadata management strategy to efficiently handle different metadata workloads. It can deliver high performance and scalable metadata service through four techniques, including directory conversion metadata, mimic hierarchical directory structure, flexible partition methods targeted different kinds of metadata of diverse characteristics, and the application of database to metadata backend. Using micro-benchmarks and a prototype system, we firstly demonstrate the performance superiority of our strategy compared to Lazy Hybrid, and then present the detailed performance results and analysis of our strategy on different MDS scales.