A reliability analysis for wireless sensor networks in a wind farm

The paper proposes Markov models for the reliability analysis of the wireless sensor networks with standby backup elements. There are presented the theoretical aspects and some of the variables that are used in the domain of fault tolerant systems. There has been conducted a study regarding the reliability of system versus cost price, considering different number of hot redundant spare parts. Reliability evaluation techniques are important in the context of design and analysis of sensitive information gathering sensor networks

[1]  Xiong Hua-gang.  On Reliability Modeling for Wireless Sensor Networks , 2008 .

[2]  Dong Seong Kim,et al.  A framework of survivability model for wireless sensor network , 2006, First International Conference on Availability, Reliability and Security (ARES'06).

[3]  M. B. Rajarshi,et al.  Bathtub distributions: a review , 1988 .

[4]  Martin L. Shooman,et al.  Reliability of computer systems and networks , 2001 .

[5]  Domenico Cotroneo,et al.  Modeling and Assessing the Dependability ofWireless Sensor Networks , 2007, 2007 26th IEEE International Symposium on Reliable Distributed Systems (SRDS 2007).

[6]  Jie Wang,et al.  Fault-Tolerant Sensor Coverage for Achieving Wanted Coverage Lifetime with Minimum Cost , 2007, International Conference on Wireless Algorithms, Systems and Applications (WASA 2007).

[7]  J. Rupe.  Reliability of Computer Systems and Networks Fault Tolerance, Analysis, and Design , 2003 .

[8]  Mohsen Sharifi,et al.  Achieving availability and reliability in wireless sensor networks applications , 2006, First International Conference on Availability, Reliability and Security (ARES'06).

[9]  Min Xie,et al.  Ch. 3. Bathtub-shaped failure rate life distributions , 2001 .

[10]  Urs Graf,et al.  Applied Laplace Transforms and z-Transforms for Scientists and Engineers: A Computational Approach using a Mathematica Package , 2004 .

[11]  Claude Chaudet,et al.  End-to-end reliability in wireless sensor networks: Survey and research challenges , 2007 .

[12]  D. P. Gaver,et al.  Analytical hazard representations for use in reliability, mortality, and simulation studies , 1979 .