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: Ali Shareef, Yifeng Zhu
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Journal of Computer Networks and Communications
Online Access:http://dx.doi.org/10.1155/2012/870281
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spelling doaj-dd6d0b5bf1d240adb9b102f05a024d7d2020-11-25T00:48:57ZengHindawi LimitedJournal of Computer Networks and Communications2090-71412090-715X2012-01-01201210.1155/2012/870281870281Effective Stochastic Modeling of Energy-Constrained Wireless Sensor NetworksAli Shareef0Yifeng Zhu1Department of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USADepartment of Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USAEnergy 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.http://dx.doi.org/10.1155/2012/870281
collection DOAJ
language English
format Article
sources DOAJ
author Ali Shareef
Yifeng Zhu
spellingShingle Ali Shareef
Yifeng Zhu
Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
Journal of Computer Networks and Communications
author_facet Ali Shareef
Yifeng Zhu
author_sort Ali Shareef
title Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
title_short Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
title_full Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
title_fullStr Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
title_full_unstemmed Effective Stochastic Modeling of Energy-Constrained Wireless Sensor Networks
title_sort effective stochastic modeling of energy-constrained wireless sensor networks
publisher Hindawi Limited
series Journal of Computer Networks and Communications
issn 2090-7141
2090-715X
publishDate 2012-01-01
description 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.
url http://dx.doi.org/10.1155/2012/870281
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AT yifengzhu effectivestochasticmodelingofenergyconstrainedwirelesssensornetworks
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