DocumentCode
1514402
Title
Automated Generation of Performance and Dependability Models for the Assessment of Wireless Sensor Networks
Author
Martino, Catello Di ; Cinque, Marcello ; Cotroneo, Domenico
Author_Institution
Dipt. di Inf. e Sist. DIS, Univ. of Naples Federico II, Naples, Italy
Volume
61
Issue
6
fYear
2012
fDate
6/1/2012 12:00:00 AM
Firstpage
870
Lastpage
884
Abstract
Wireless Sensor Networks (WSNs) are widely recognized as a promising solution to build next-generation monitoring systems. Their industrial uptake is however still compromised by the low level of trust on their performance and dependability. Whereas analytical models represent a valid mean to assess nonfunctional properties via simulation, their wide use is still limited by the complexity and dynamicity of WSNs, which lead to unaffordable modeling costs. To reduce this gap between research achievements and industrial development, this paper presents a framework for the assessment of WSNs based on the automated generation of analytical models. The framework hides modeling details, and it allows designers to focus on simulation results to drive their design choices. Models are generated starting from a high-level specification of the system and by a preliminary characterization of its fault-free behavior, using behavioral simulators. The benefits of the framework are shown in the context of two case studies, based on the wireless monitoring of civil structures.
Keywords
monitoring; wireless sensor networks; WSN; analytical models; automated generation; fault-free behavior; industrial development; next-generation monitoring systems; wireless monitoring; wireless sensor network assessment; Analytical models; Complexity theory; Computational modeling; Hardware; Routing; Unified modeling language; Wireless sensor networks; WSN design.; Wireless sensor networks dependability; assessment framework; stochastic activity networks;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/TC.2011.96
Filename
5765942
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