Using PR-Tree and HPIR to Manage Coherence of Semantic Cache for Location Dependent Data in Mobile Database

  • Shengfei Shi
  • Jianzhong Li
  • Chaokun Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2419)

Abstract

Location dependent data (LDD) is the data whose value is determined by the location to which it is related. In LDD system, caching is a crucial way to improve the performance because a new query can be partially answered locally when the client is continuously moving around. Semantic caching has been paid much attention in traditional database systems. However, the methods of semantic cache management proposed in those systems are not suitable for mobile computing environment. Moreover, although many improved semantic caching strategies for mobile computing application have been proposed in recent years, few papers discussed semantic cache coherence control, which is very important in mobile computing environment. In this paper, we propose PR-tree and HPIR based algorithm, which can significantly reduce the unnecessary uplink requests and downlink broadcasts compared to previous PIR based schemes. Simulation experiments are carried out to evaluate the proposed strategy.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Qun Ren, Margaret H. Dunham: Using semantic caching to manage location dependent data in mobile computing. MOBICOM (2000) 210–221Google Scholar
  2. 2.
    AY. Seydim, MH. Dunham, V Kumar: Location Dependent Query Processing. MoBiDe (2001) 47–53Google Scholar
  3. 3.
    S. Dar, et al: Semantic Data Caching and Replacement. Proc. VLDB (1996) 330–341Google Scholar
  4. 4.
    AM. Keller, Julie Basu: A predicate-based caching scheme for client-server database architectures. VLDB Journal (1996) 5:35–47CrossRefGoogle Scholar
  5. 5.
    Q Ren, MH. Dunham: Using Clustering for Effective Management of a Semantic Cache in Mobile Computing. MoBiDe (1999) 94–101Google Scholar
  6. 6.
    Guohong Cao: A Scalable Low-Latency Cache Invalidation Strategy for Mobile Environments. ACM MOBICOM (2000) 200–209Google Scholar
  7. 7.
    D. Barbara and T. Imielinkai, Sleepers and workaholics: Caching strategies for mobile environments. ACM SIGMOD (1994) 1–12Google Scholar
  8. 8.
    T. Imielinksi, S. Viswanathan, and B. Badrinath: Energy Effcient Indexing on Air. IEEE Transactions on Knowledge and Data Engineering 1997 9(3): 353–372CrossRefGoogle Scholar
  9. 9.
    G. Forman and J. Zahorjan: The Challenges of Mobile Computing. IEEE Computer (1994), 27(6) 38–47Google Scholar
  10. 10.
    YD Chung et al: Predicate-based Cache Management for Continuous Partial Match Queries in Mobile Databases. KAIST CS Technical Report CS/TR-2001-163Google Scholar
  11. 11.
    P. Godfrey and J. Grys: Semantic query caching in heterogeneous databases. In Proceedings of KRDB at VLDB (1997) 6.1–6.6Google Scholar
  12. 12.
    K.C.K. Lee, H.V. Leong, and A. Si: Semantic query caching in a mobile environment. Mobile Computing and Communications Review, 1999 3(2) 28–36CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Shengfei Shi
    • 1
  • Jianzhong Li
    • 1
  • Chaokun Wang
    • 1
  1. 1.Department of Computer Science and EngineeringHarbin Institute of TechnologyHarbin, HeilongjiangChina

Personalised recommendations