1st International ICST Workshop on Advances in Sensor Networks

Research Article

Optimal Actuation Strategies for Sensor/Actuator Networks

  • @INPROCEEDINGS{10.1109/MOBIQ.2006.340389,
        author={F.  Thouin and R. Thommes and M.J.  Coates},
        title={Optimal Actuation Strategies for Sensor/Actuator Networks},
        proceedings={1st International ICST Workshop on Advances in Sensor Networks},
        publisher={IEEE},
        proceedings_a={IWASN},
        year={2007},
        month={4},
        keywords={},
        doi={10.1109/MOBIQ.2006.340389}
    }
    
  • F. Thouin
    R. Thommes
    M.J. Coates
    Year: 2007
    Optimal Actuation Strategies for Sensor/Actuator Networks
    IWASN
    IEEE
    DOI: 10.1109/MOBIQ.2006.340389
F. Thouin1, R. Thommes1, M.J. Coates1
  • 1: Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, Que.

Abstract

Wireless sensor-actuator networks (SANETs), in which nodes perform actions (actuation) in response to sensor measurements and shared information, have great potential in medical and agricultural applications. In this paper, we focus on the problem of using distributed sensed data to design actuation strategies in order to elicit a desired response from the environment, whilst attempting to minimize the communication in the network. Our methodology is based on batch Q-learning; we describe a distributed approach for learning dyadic regression trees to estimate the Q-functions from collected data. Analysis and simulation indicate that substantial communication savings that can be achieved through distributed learning without significant performance deterioration. The simulations also reveal that the performance of our technique depends strongly on the amount of training data available