Autonomous clustering for wireless sensor networks

  • Authors:
  • Fabian D. Winter;Peer Kröger;Johannes Niedermayer;Matthias Renz

  • Affiliations:
  • Ludwig-Maximilians University, Munich, Germany;Ludwig-Maximilians University, Munich, Germany;Ludwig-Maximilians University, Munich, Germany;Ludwig-Maximilians University, Munich, Germany

  • Venue:
  • Proceedings of the 25th International Conference on Scientific and Statistical Database Management
  • Year:
  • 2013

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Abstract

Most algorithms treat Wireless Sensor Networks (WSNs) only as a generator of data without any autonomy. In contrast to this approach, we propose the ACIDE framework: A completely decentralized, bottom-up clustering process and information exchange that does not depend on given infrastructure such as fixed root nodes. While it has slightly higher requirements for the nodes, its dynamic and independent nature has many advantages, such as the user beeing able to initiate queries from any point in the network rather than being limited to query the network through an a priori fixed sink node. The framework can deal with changing environments and energy depletion. Through careful abstraction, we also support customization and adaption to different environments.