• DocumentCode
    3323655
  • Title

    XStream: a Signal-Oriented Data Stream Management System

  • Author

    Girod, Lewis ; Mei, Yuan ; Newton, Ryan ; Rost, Stanislav ; Thiagarajan, Arvind ; Balakrishnan, Hari ; Madden, Samuel

  • Author_Institution
    Comput. Sci. & Artificial Intell. Lab., MIT, Cambridge, MA
  • fYear
    2008
  • fDate
    7-12 April 2008
  • Firstpage
    1180
  • Lastpage
    1189
  • Abstract
    Sensors capable of sensing phenomena at high data rates on the order of tens to hundreds of thousands of samples per second are now widely deployed in many industrial, civil engineering, scientific, networking, and medical applications. In aggregate, these sensors easily generate several million samples per second that must be processed within milliseconds or seconds. The computation required includes both signal processing and event stream processing. XStream is a stream processing system for such applications. XStream introduces a new data type, the signal segment, which allows applications to manipulate isochronous (regularly spaced in time) collections of sensor samples more conveniently and efficiently than the asynchronous representation used in previous work. XStream includes a memory manager and scheduler optimizations tuned for processing signal segments at high speeds. In benchmark comparisons, we show that XStream outperforms a leading commercial stream processing system by more than three orders of magnitude. On one application, the commercial system processed 72.7 Ksamples/sec, while XStream processed 97.6 Msamples/sec.
  • Keywords
    database management systems; optimisation; sensor fusion; data stream management system; event stream processing; memory manager optimization; scheduler optimization; sensor; signal processing; Acoustic signal processing; Aggregates; Computer network management; Filters; Intelligent sensors; Memory management; Performance gain; Sensor phenomena and characterization; Signal design; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4244-1836-7
  • Electronic_ISBN
    978-1-4244-1837-4
  • Type

    conf

  • DOI
    10.1109/ICDE.2008.4497527
  • Filename
    4497527