Performance Analysis of Sleep Scheduling Schemes in Sensor Networks using Stochastic Petri Net

As the most important issue in wireless sensor networks, power saving is catching researchers´ great attentions all the time. Among several power saving strategies, one of the best methods is to make unused components inactive whenever possible, i.e. applying sleep scheduling schemes to sensors. In this paper, by analyzing and concluding existing works, we propose four sleep scheduling schemes (ACAA, SRAA, SAA and NCAA) for different kinds of application environments, then analyze each of them by stochastic petri net (SPN). We can easily get the average power consumptions and event delays of sensor nodes by using the steady state probability matrix of the SPN models. Moreover, the numeric results show that this concise graphic analysis method is suitable for analyzing sleep scheduling schemes.