• DocumentCode
    2005236
  • Title

    Scalable data fusion using Astrolabe

  • Author

    Birman, Kenneth P. ; Van Renesse, Robbert ; Vogels, Werner

  • Author_Institution
    Cornell Univ., Ithaca, NY, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    8-11 July 2002
  • Firstpage
    1434
  • Abstract
    The dramatic growth of computer networks creates both an opportunity and a daunting distributed computing problem for users seeking to perform data fusion and data mining. The problem is that data often resides on large numbers of devices and evolves rapidly. Systems that collect data at a single location scale poorly and suffer from single-point-failures. Astrolabe performs data fusion in real-time, creating a virtual system-wide hierarchical database, which evolves as the underlying information changes. A scalable aggregation mechanism offers a flexible way to perform data mining within the resulting virtual database. Astrolabe is secure, robust under a wide range of failure and attack scenarios, and imposes low loads even under stress.
  • Keywords
    data mining; database management systems; distributed processing; real-time systems; sensor fusion; attack scenarios; computer networks; data collection; data mining; distributed computing; distributed computing problem; hierarchical databases; low loads; peer-to-peer communication; real-time data fusion; scalable aggregation mechanism; scalable data fusion; single-point failures; virtual system-wide hierarchical database; Application software; Biosensors; Data mining; Data security; Databases; Distributed computing; Peer to peer computing; Protocols; Robustness; Scalability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2002. Proceedings of the Fifth International Conference on
  • Conference_Location
    Annapolis, MD, USA
  • Print_ISBN
    0-9721844-1-4
  • Type

    conf

  • DOI
    10.1109/ICIF.2002.1020984
  • Filename
    1020984