Energy consumption of energy-constrained nodes in wireless sensor networks (WSNs) is a fatal#R##N#weakness of these networks. Since these nodes usually operate on batteries, the maximum utility of the#R##N#network is dependent upon the optimal energy usage of these nodes. However, new emerging optimal#R##N#energy consumption algorithms, protocols, and system designs require an evaluation platform. This#R##N#necessitates modeling techniques that can quickly and accurately evaluate their behavior and identify#R##N#strengths and weakness. We propose Petri nets as this ideal platform. We demonstrate Petri net#R##N#models of wireless sensor nodes that incorporate the complex interactions between the processing and#R##N#communication components of an WSN. These models include the use of both an open and closed workload#R##N#generators. Experimental results and analysis show that the use of Petri nets is more accurate than the#R##N#use of Markov models and programmed simulations. Furthermore, Petri net models are extremely easier#R##N#to construct and test than either. This paper demonstrates that Petri net models provide an effective#R##N#platform for studying emerging energy-saving strategies in WSNs.
['Ali Shareef', 'Yifeng Zhu']
Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks