• DocumentCode
    1168576
  • Title

    Detecting application-level failures in component-based Internet services

  • Author

    Kiciman, Emre ; Fox, Armando

  • Author_Institution
    Dept. of Comput. Sci., Stanford Univ., CA, USA
  • Volume
    16
  • Issue
    5
  • fYear
    2005
  • Firstpage
    1027
  • Lastpage
    1041
  • Abstract
    Most Internet services (e-commerce, search engines, etc.) suffer faults. Quickly detecting these faults can be the largest bottleneck in improving availability of the system. We present Pinpoint, a methodology for automating fault detection in Internet services by: 1) observing low-level internal structural behaviors of the service; 2) modeling the majority behavior of the system as correct; and 3) detecting anomalies in these behaviors as possible symptoms of failures. Without requiring any a priori application-specific information, Pinpoint correctly detected 89%-96% of major failures in our experiments, as compared with 20%-70% detected by current application-generic techniques.
  • Keywords
    Internet; authorisation; information services; Pinpoint; anomaly detection; application-generic techniques; application-level failures; component-based Internet services; e-commerce; fault detection; search engines; Application software; Availability; Computer science; Computerized monitoring; Condition monitoring; Fault detection; Prototypes; Search engines; Testing; Web and internet services; Anomaly detection; Internet services; application-level failures; Algorithms; Artifacts; Artificial Intelligence; Computer Simulation; Information Storage and Retrieval; Internet; Models, Statistical; Pattern Recognition, Automated; Signal Processing, Computer-Assisted; Telecommunications;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2005.853411
  • Filename
    1510707