A new self-diagnosing approach based on petri nets and correlation graphs for fault management in wireless sensor networks

2013 ◽  
Vol 59 (8) ◽  
pp. 582-600 ◽  
Author(s):  
Shahram Babaie ◽  
Afsaneh Khosrohosseini ◽  
Ahmad Khadem-Zadeh
2007 ◽  
Vol 14 (6) ◽  
pp. 13-19 ◽  
Author(s):  
Mengjie Yu ◽  
Hala Mokhtar ◽  
Madjid Merabti

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Ali Shareef ◽  
Yifeng Zhu

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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