• DocumentCode
    1299532
  • Title

    RFID Data Processing in Supply Chain Management Using a Path Encoding Scheme

  • Author

    Lee, Chun-Hee ; Chung, Chin-Wan

  • Author_Institution
    Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
  • Volume
    23
  • Issue
    5
  • fYear
    2011
  • fDate
    5/1/2011 12:00:00 AM
  • Firstpage
    742
  • Lastpage
    758
  • Abstract
    RFID technology can be applied to a broad range of areas. In particular, RFID is very useful in the area of business, such as supply chain management. However, the amount of RFID data in such an environment is huge. Therefore, much time is needed to extract valuable information from RFID data for supply chain management. In this paper, we present an efficient method to process a massive amount of RFID data for supply chain management. We first define query templates to analyze the supply chain. We then propose an effective path encoding scheme that encodes the flows of products. However, if the flows are long, the numbers in the path encoding scheme that correspond to the flows will be very large. We solve this by providing a method that divides flows. To retrieve the time information for products efficiently, we utilize a numbering scheme for the XML area. Based on the path encoding scheme and the numbering scheme, we devise a storage scheme that can process tracking queries and path oriented queries efficiently on an RDBMS. Finally, we propose a method that translates the queries to SQL queries. Experimental results show that our approach can process the queries efficiently.
  • Keywords
    SQL; XML; query processing; radiofrequency identification; supply chain management; RDBMS; RFID data processing; SQL queries; XML area; numbering scheme; path encoding scheme; path oriented queries; query templates; storage scheme; supply chain management; tracking queries; Encoding; RFID tags; Servers; Supply chain management; Supply chains; XML; RFID; path encoding scheme; prime number.; supply chain management;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2010.136
  • Filename
    5551135