Analysis of On-off policies in Sensor Networks Using Interacting Markovian Agents

Power management in battery operated sensor networks, is a hot topic addressed by many ongoing researches. One of the most commonly employed technique consists in turning on and of the power of the radio unit to reduce the power consumption. In this paper we exploit the modelling power of Interacting Markovian agent to evaluate the performance of four different on-off strategies. A Markovian agent (MA) is an entity whose behaviour is described by a continuous time Markov chain (CTMC) and that is able to interact with other MA's by sending and receiving messages. A perceived message may induce a state transition in an MA according to a perception function than can depend on the geographical location of the MA's, on the message routing strategy and on the transmission property of the medium. We represent each sensor by an MA and we show how MA's can interact to produce the collective behaviour of the sensor network.