• DocumentCode
    168491
  • Title

    Efficient Agile Sink Selection in Wireless Sensor Networks Based on Compressed Sensing

  • Author

    Mahmudimanesh, Mohammadreza ; Naseri, Amir ; Suri, Neeraj

  • Author_Institution
    Tech. Univ. of Darmstadt, Darmstadt, Germany
  • fYear
    2014
  • fDate
    26-28 May 2014
  • Firstpage
    193
  • Lastpage
    200
  • Abstract
    Collection of the sensed data in a wireless sensor network at one or more sink (s) is a well studied problem and there are a lot of efficient solutions for a variety of wireless sensor network configurations and application requirements. These methods are often optimized towards collection of the sensed data at a predetermined base station or sink. This inherently reduces the agility of the wireless sensor network as the flow of information is not easily changeable after the establishment of the routing and data collection algorithms. This paper presents an efficient data dissemination method based on the compressed sensing theory that allows each sensor node to take the role of a sink. Agile sink selection is especially advantageous in scenarios where the sink or the end user of the wireless sensor network is mobile. The proposed method allows availing the global state of the environment by fetching a small set of data from any arbitrary node. Our evaluations prove the better performance of our technique over existing methods. Also a comparison with an oracle-based approach gives sufficient experimental evidences of a nearly optimal performance of our method.
  • Keywords
    compressed sensing; telecommunication network routing; wireless sensor networks; agile sink selection; arbitrary node; base station; compressed sensing; data dissemination; global state; oracle-based approach; routing; sensed data collection; wireless sensor networks; Coherence; Generators; Protocols; Sensors; Tin; Vectors; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing in Sensor Systems (DCOSS), 2014 IEEE International Conference on
  • Conference_Location
    Marina Del Rey, CA
  • Type

    conf

  • DOI
    10.1109/DCOSS.2014.21
  • Filename
    6846165