Dynamic definition of the sampling rate of data in Wireless Sensor Network with Adaptive Automata

Abstract

The Wireless Sensor Networks have the potential for different applications, especially for environmental monitoring. This paper aims to present the formalization of a technique to minimize the energy expenditure of sensor nodes in a Wireless Sensor Network. The technique presented considers the use of Adaptive Automata and the possibility of the sensor network dynamically vary the interval (time) between a data logging and other. Thus, it is expected that the sensor network automatically use long intervals while collecting information within a range of values considered normal or acceptable. However, when the nodes collect data considered outside the normal range, it is expected that the data sampling intervals are reduced, so that the sensor network to monitor the phenomenon in more detail. With the implementation of this strategy is economy in energy consumption of sensor nodes in the network without loss of efficiency in the monitoring of phenomena. The formalization of the technique is given by Adaptive Automata that has adaptive actions to dynamically adjust the sampling interval of sensor nodes. To verify the energy savings was developed and evaluated a computational simulation results.