Experimental Evaluation of Dynamic Data Allocation Strategies in a Distributed Database With Changing Workloads.

Abstract

Traditionally, allocation of data in distributed database management systems has been determined by off-line analysis and optimization. This technique works well for static database access patterns, but is often inadequate for frequently changing workloads. In this paper we address how to dynamically reallocate data for partionable distributed databases with changing access patterns. Rather than complicated and expensive optimization algorithms, a simple heuristic is presented and shown, via an implementation study, to improve system throughput by 30% in a local area network based system. Based on artificial wide area network delays, we show that dynamic reallocation can improve system throughput by a factor of two and a half for wide area networks. We also show that individual site load must be taken into consideration when reallocating data, and provide a simple policy that incorporates load in the reallocation decision.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA292175

Entities

People

  • Anna Brunstrom
  • Rahul Simha
  • Scott T. Leutenegger

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Climate Change
  • Computer Networks
  • Computer Programs
  • Computer Science
  • Computers
  • Database Management Systems
  • Databases
  • Engineering
  • Local Area Networks
  • Networks
  • Optimization
  • Relational Databases
  • Statistics
  • Test And Evaluation
  • Throughput
  • Wide Area Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Database Systems and Applications
  • Economics