First International ICST Workshop on Cognitive Radio and Cooperative Strategies for Power Saving

Research Article

Energy Efficient Trade-Off between Communication and Sensing in Wireless Gas Sensor Node

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  • @INPROCEEDINGS{10.1007/978-3-642-35155-6_39,
        author={Andrey Somov and Mikhail Ivanov and Alexander Baranov and Alexey Savkin and Sithamparanathan Kandeepan},
        title={Energy Efficient Trade-Off between Communication and Sensing in Wireless Gas Sensor Node},
        proceedings={First International ICST Workshop on Cognitive Radio and Cooperative Strategies for Power Saving},
        proceedings_a={C2POWER},
        year={2012},
        month={12},
        keywords={energy efficient communication wireless sensor node power management gas sensor},
        doi={10.1007/978-3-642-35155-6_39}
    }
    
  • Andrey Somov
    Mikhail Ivanov
    Alexander Baranov
    Alexey Savkin
    Sithamparanathan Kandeepan
    Year: 2012
    Energy Efficient Trade-Off between Communication and Sensing in Wireless Gas Sensor Node
    C2POWER
    Springer
    DOI: 10.1007/978-3-642-35155-6_39
Andrey Somov1,*, Mikhail Ivanov2,*, Alexander Baranov2, Alexey Savkin2, Sithamparanathan Kandeepan1,*
  • 1: CREATE-NET, Networks and Services Area
  • 2: Moscow State Aviation Technological University
*Contact email: andrey.somov@create-net.org, radio@mati.ru, kandee@create-net.org

Abstract

A wireless sensor network is a distributed collection of resource constrained tiny nodes capable of operating with minimal user attendance. Communication circuit is normally the most power consuming part of sensor node. Depending on the application, the node may have on board various extra hardware components with even higher power consumption. These components can impose restrictions in terms of providing the same communication range without increasing power consumption. In this paper we investigate the energy efficient balance between the communication and sensing modes in a gas sensor node. First, we analyze how to secure the energy efficient sensing of environment using the developed framework. Then we establish the efficient transmission power rate for each sensing power level. Finally, the effective distances for the appropriate transmission rates are defined.