Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Computer Networks and Communications |
| Online Access: | http://dx.doi.org/10.1155/2012/870281 |
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| Summary: | 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. |
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| ISSN: | 2090-7141 2090-715X |