Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks

Energy consumption of energy-constrained nodes in wireless sensor networks (WSNs) is a fatalweakness of these networks. Since these nodes usually operate on batteries, the maximum utility of thenetwork is dependent upon the optimal energy usage of these nodes. However, new emerging optimalenergy consumption algorithms, protocols, and system designs require an evaluation platform. Thisnecessitates modeling techniques that can quickly and accurately evaluate their behavior and identifystrengths and weakness. We propose Petri nets as this ideal platform. We demonstrate Petri netmodels of wireless sensor nodes that incorporate the complex interactions between the processing andcommunication components of an WSN. These models include the use of both an open and closed workloadgenerators. Experimental results and analysis show that the use of Petri nets is more accurate than theuse of Markov models and programmed simulations. Furthermore, Petri net models are extremely easierto construct and test than either. This paper demonstrates that Petri net models provide an effectiveplatform for studying emerging energy-saving strategies in WSNs