Evaluating causal relationships in wireless sensor/actuator networks

This paper addresses the evaluation of causal relationships in large-scale wireless sensor/actuator networks (WSANs). WSANs consist of nodes that can monitor the environment (sensors), actively interact with the environment (actuators), or perform both functions. Such networks, together with the monitored environment, form complex, large-scale dynamic systems. It can be important to identify the causal relationships between variables in these systems; this provides individual actuator nodes with information about the probable consequences of local action on the global monitored environment. Such knowledge is critical to the formation of coordinated action plans, as might be required, for example, in distributed treatment strategies in medical or agricultural applications. 1