Markovian Agent models for wireless sensor networks deployed in environmental protection

Wireless Sensor Networks (WSN) are distributed interacting systems formed by many similar tiny sensors communicating to gather information from the environment and transmit it to a base station. The present paper presents an analytical modeling and analysis technique based on Markovian Agents (MAs) and discusses a very complex scenario in which a WSN is deployed in a wide open area to monitor the outbreak of a fire and send a warning signal to a base station. The models is composed by four classes of MA modeling, respectively: the fire propagation, the high temperature front propagation, the sensor nodes and the sink; and four types of messages. It is shown that, even if the overall state space of the models is huge, nevertheless an analytical solution is feasible, by exploiting the locality of the interactions among MAs, based on a message passing mechanism combined with a perception function.