Selective-Splitting and Cache-Maintenance Algorithms for Associative-Client Caches

  • Authors:
  • Jiaxin J. Gao;Dallan Quass;Yiu-Kai Ng

  • Affiliations:
  • Tenfold Corp., Draper, UT 84020;Comp. Sci. Dept., Brigham Young Univ., Provo, UT 84602;Comp. Sci. Dept., Brigham Young Univ., Provo, UT 84602. ng@cs.byu.edu

  • Venue:
  • Distributed and Parallel Databases
  • Year:
  • 2004

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Abstract

We propose a number of selective-splitting and cache-maintenance algorithms to reduce the computational complexity of associative-client caches and network load. Our selective-splitting algorithms selectively split query-intersected semantic regions based on the relative region access-latency or relative region size in a semantic data caching and replacement model. Our cache-maintenance algorithms are set up for studying a variety of design issues in synchronizing associative-client caches. We analyzed the performance of our proposed algorithms in a network environment. Results from our study show that the selective-splitting algorithms reduce the number of splitting operations by 80% in most cases, and the avoidance-based maintenance algorithms outperform the detection-based maintenance algorithms not only in reducing the network traffic but also in rendering consistent performance under various experimental variances.