• DocumentCode
    2617771
  • Title

    Stream ancestor function: A mechanism for fine-grained provenance in stream processing systems

  • Author

    Sansrimahachai, Watsawee ; Weal, Mark J. ; Moreau, Luc

  • Author_Institution
    Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK
  • fYear
    2012
  • fDate
    16-18 May 2012
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    Applications that require continuous processing of high-volume data streams have grown in prevalence and importance. These systems process streaming data in real-time and provide instantaneous response to support precise and ontime decisions. In such systems, it is difficult to know exactly how a particular result is generated or more particularly how to precisely trace stream events that caused a particular result. However, such information is extremely important for validating stream processing results. Therefore, it is crucial that stream processing systems have a mechanism for capturing and querying provenance information - the information pertaining to the process that produced result data - at the level of individual stream events, which we refer to as fine-grained provenance. In this paper, we propose a novel fine-grained provenance solution called Stream Ancestor Function - a reverse mapping function used to express precise dependencies between input and output stream elements. We demonstrate how to utilize stream ancestor functions by means of a stream provenance query and replay execution algorithm. Finally, we evaluate the stream ancestor function in terms of storage consumption for provenance collection and system throughput, demonstrating significant reductions in storage size and reasonable processing overheads.
  • Keywords
    query processing; storage management; continuous high-volume data stream processing; fine-grained provenance; input stream elements; ontime decision support; output stream elements; precise decision support; processing overheads; provenance collection; provenance information querying; real-time streaming data processing; replay execution algorithm; reverse mapping function; storage consumption; storage size; stream ancestor function; stream provenance querying; system throughput; Computational modeling; Delay; Geographic information systems; Production; Real time systems; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research Challenges in Information Science (RCIS), 2012 Sixth International Conference on
  • Conference_Location
    Valencia
  • ISSN
    2151-1349
  • Print_ISBN
    978-1-4577-1936-3
  • Electronic_ISBN
    2151-1349
  • Type

    conf

  • DOI
    10.1109/RCIS.2012.6240427
  • Filename
    6240427