Mining Frequent Patterns in Wireless Sensor Network Configurations

  • Da-Ren Chen
  • Shu-Ming Hsieh
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 309)

Abstract

Graph is suitable for modeling many emerging fields such as configuring a wireless sensor network. The graph databases which representing the underlying real-world structures may therefore possess abounding unknown knowledge waiting to be discovered. Consequently, how to automatically mining the hidden information from these graph databases becomes critical for many new and promising applications. This paper proposes a new algorithm MFG (Mining Frequent subGraph patterns), which employs the global orders of labels in molecular graph patterns, in cooperation with fast pruning mechanisms, to reduce the amount of duplicated candidate enumeration. MFG also utilizes several effective data structures to store the subgraph pattern embedding information. By these proposed techniques, MFG shows its benefits such as it reduces candidate duplication dramatically, eliminates subgraph isomorphism checking completely, and alleviates the cost of graph isomorphism testing. The conducted experimental results show that MFG works with more economical memory consumption and better efficiency compared with a state-of-the-art mining method.

Keywords

wireless sensor network algorithm graph mining frequent patterns 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Da-Ren Chen
    • 1
  • Shu-Ming Hsieh
    • 2
  1. 1.Department of Information ManagementNational Taichung University of Science and TechnologyTaichungTaiwan, R.O.C.
  2. 2.Department of Computer Science and Information EngineeringHwa Hsia Institute of TechnologyTaipeiTaiwan

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