Periodic Associated Sensor Patterns Mining from Wireless Sensor Networks

  • Md. Mamunur RashidEmail author
  • Joarder Kamruzzaman
  • Iqbal Gondal
  • Rafiul Hassan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10638)


Mining interesting knowledge from the massive amount of data gathered in wireless sensor networks is a challenging task. Works reported in literature all-confidence measure based associated sensor patterns can captures association-like co-occurrences and the strong temporal correlations implied by such co-occurrences in the sensor data. However, when the user given all-confidence threshold is low, a huge amount of patterns are generated and mining these patterns may not be space and time efficient. Temporal periodicity of pattern appearance can be regarded as an important criterion for measuring the interestingness of associated patterns in WSNs. Associated sensor patterns that occur after regular intervals is called periodic associated sensor patterns. Even though mining periodic associated sensor patterns from sensor data stream is extremely important in many real-time applications, no such algorithm has been proposed yet. In this paper, we propose a compact tree structure called Periodic Associated Sensor Pattern-tree (PASP-tree) and an efficient mining approach for finding periodic associated sensor patterns (PASPs) from WSNs. Extensive performance analyses show that our technique is time and memory efficient in finding periodic associated sensor patterns.


Wireless sensor networks Data mining Periodicity Knowledge discovery Associated sensor pattern 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Md. Mamunur Rashid
    • 1
    Email author
  • Joarder Kamruzzaman
    • 1
    • 2
  • Iqbal Gondal
    • 1
    • 2
  • Rafiul Hassan
    • 3
  1. 1.Faculty of Information TechnologyMonash UniversityClaytonAustralia
  2. 2.ICSLFederation UniversityBallaratAustralia
  3. 3.King Fahd University of Petroleum and MineralsDhahranSaudi Arabia

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