Efficient detection of motion-trend predicates in wireless sensor networks

Besim Avci*, Goce Trajcevski, Roberto Tamassia, Peter Scheuermann, Fan Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This work addresses the problem of efficient distributed detection of predicates capturing the motion trends of mobile objects evaluated with respect to a (boundary of a) polygonal region, in the settings in which the (location, time) data is obtained via tracking in Wireless Sensor Networks (WSN). Specifically, we discuss in-network distributed algorithms for detecting two motion-trend predicates: Continuously Moving Towards and Persistently Moving Towards: first for a single object, and then the corresponding variants for multiple objects. We also present methodologies which consider the energy vs. latency trade-offs when multiple tracked objects are being considered for validating the monitored predicates. Our experiments demonstrate that our proposed technique yield substantial energy savings when compared to the naïve centralized and cluster-based approaches in which the raw (location, time) data is transmitted to a dedicated sink where the predicates are being evaluated.

Original languageEnglish (US)
Pages (from-to)26-43
Number of pages18
JournalComputer Communications
Volume101
DOIs
StatePublished - Mar 15 2017

Keywords

  • Data aggregation
  • Distributed algorithms
  • Motion trends
  • Spatial data
  • WSN
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications

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