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Journal of Computer Networks and Communications
Volume 2012 (2012), Article ID 870281, 20 pages
Research Article

Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks

Department of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USA

Received 16 June 2012; Accepted 11 September 2012

Academic Editor: Runhua Chen

Copyright © 2012 Ali Shareef and Yifeng Zhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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