• DocumentCode
    1780397
  • Title

    Weighted Category Matching Algorithm in Sensor Cloud for rapid retrieval

  • Author

    Ramachandran, Siddharth ; Grace, S. Shakena ; Beevi, S. Sarjun

  • Author_Institution
    Dept. of Inf. Technol., Anna Univ., Chennai, India
  • fYear
    2014
  • fDate
    10-12 April 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Sensor-cloud is a relatively new interdisciplinary domain that combines the fields of Wireless Sensor Networks (WSN) and Cloud Computing. The major issue needs to be addressed in Sensor-Cloud is storage and retrieval of data. Data security is preserved by encrypting the sensor data before storing it into the cloud. On analysis of existing methods, there are two different issues, First issue; Encrypted Document matching is performed based on their plaintext keywords which is not suitable for sensor data and Second issue, subscribers are categorized based on their predicates. So, the storage space required is more. To overcome these issues, the paper proposes a new indexing structure which is suitable for sensor data and a new algorithm called Weighted Category Matching Algorithm (WCMA) for quick retrieval. On comparing with existing methods, the proposed WCMA algorithm achieves a better document retrieval and results are discussed in implementation details.
  • Keywords
    cloud computing; cryptography; information retrieval; sensor fusion; string matching; WCMA; WSN; cloud computing; data security; data storage; document retrieval; encrypted document matching; sensor cloud; weighted category matching algorithm; wireless sensor networks; Cloud computing; Cryptography; Indexes; Keyword search; Servers; Subscriptions; Wireless sensor networks; Cloud storage; Ranking; WSN; event matching; publisher/subscriber;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Trends in Information Technology (ICRTIT), 2014 International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1109/ICRTIT.2014.6996148
  • Filename
    6996148