research-article

Dynamic hybrid fault models and the applications to wireless sensor networks (WSNs)

Authors:

Zhanshan (Sam) Ma,

Axel W. KringsAuthors Info & Claims

MSWiM '08: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems

Pages 100 - 108

https://doi.org/10.1145/1454503.1454524

Published: 27 October 2008 Publication History

Abstract

In this paper, we introduce a new concept termed dynamic hybrid fault models together with the mathematic models and approaches for applying the new concept to reliability and fault tolerance analyses. It extends the traditional hybrid fault models and their relevant constraints in agreement algorithms with survival analysis and evolutionary game theory. The new dynamic hybrid fault models (i) transform hybrid fault models into time and covariate dependent models; (ii) make real-time prediction of reliability more realistic and allows for real-time prediction of fault-tolerance; (iii) set the foundations for integrating hybrid fault models with reliability and survivability analyses by introducing evolutionary game modeling; (iv) extend evolutionary game theory in its modeling of the survivals of game players. The application domain is wireless sensor network (WSN), but the large part of the modeling architecture also applies to general engineering reliability and network survivability.

References

[1]

Azadmanesh, M. H. and R. M. Kieckhafer, 2000. Exploiting Omissive Faults in Synchronous Approximate Agreement, IEEE Trans. Computers, 49(10), pp. 1031--1042, Oct. 2000.

Digital Library

[2]

Cox, D. R. 1972. Regression models and life tables. J. R. Stat. Soc. Ser. B. 34:184--220.

[3]

Hofbauer, J. and K. Sigmund. 1998. Evolutionary Games and Population Dynamics. Cambridge University Press. 323pp.

[4]

Kalbfleisch, J. D., and R. L. Prentice, 2002. The Statistical Analysis of Failure Time Data. Wiley-InterScience, 2nd ed. 462pp.

[5]

Klein, J. P. and M. L. Moeschberger. 2003. Survival analysis techniques for censored and truncated data. Springer.

[6]

Kot, M. 2001. Elements of Mathematical Ecology. Cambridge University Press. 453pp.

[7]

Krings, A. W. and Z. S. Ma. 2006. Fault-Models in Wireless Communication: Towards Survivable Ad Hoc Networks, MILCOM 2006, Military Communications Conference, 23-25 October, 2006. 7 pages.

Digital Library

[8]

Lamport, L., R. Shostak and M. Pease. 1982. The Byzantine Generals Problem. ACM Transactions on Programming Languages and Systems, 4(3):382--401, July 1982

Digital Library

[9]

Lawless, J. F. 2003. Statistical models and methods for lifetime data. John Wiley & Sons. 2nd ed. 630pp.

[10]

Ma, Z. S. and E. J. Bechinski. 2008. A Survival-Analysis based Simulation Model for Russian Wheat Aphid Population Dynamics. Ecological Modeling 2008, 216(2):323--332

[11]

Ma, Z. S. and A. W. Krings. 2008a. Survival Analysis Approach to Reliability, Survivability and Prognostics and Health Management. Proceedings of 2008 Proc. IEEE-AIAA AeroSpace Conf. BigSky, Montana, March 1-8, 2008. 20pages.

[12]

Ma, Z. S. and A. W. Krings. 2008b. Competing Risks Analysis of Reliability, Survivability, and Prognostics and Health Management (PHM), Proc. IEEE-AIAA AeroSpace Conference, March 1-8, Big Sky, MT, 2008. 20pages.

[13]

Ma, Z. S. and A. W. Krings. 2008c. Multivariate Survival Analysis (I): Shared Frailty Approaches to Reliability and Dependence Modeling", Proc. IEEE-AIAA AeroSpace Conference, March 1-8, Big Sky, MT, 2008. 21pages.

[14]

Ma, Z. S. and A. W. Krings. 2008d. Bio-Robustness and Fault Tolerance: A New Perspective on Reliable, Survivable and Evolvable Network Systems, Proc. IEEE-AIAA AeroSpace Conference, March 1-8, Big Sky, MT, 2008. 20 pages.

[15]

Ma, Z. S. 2008. New Approaches to Reliability and Survivability with Survival Analysis, Dynamic Hybrid Fault Models and Evolutionary Game Theory. Ph.D. Dissertation, University of Idaho.

Digital Library

[16]

Martinussen, T. and T. H. Scheike. 2006. Dynamic Regression Models for Survival Data. Springer. 466pp.

[17]

Meyer, F. J. and D. K. Pradhan, 1987. Consensus with dual failure modes," Tech. Rep., Dep. Elec. Comput. Eng., Univ. Massachusetts, Amherst, MA, Apr. 1987.

[18]

Pease, M., R. Shostak, L. Lamport. 1980. Reaching Agreement in the Presence of Faults, Journal of the ACM (JACM), v.27 n.2, p.228--234, April 1980.

Digital Library

[19]

Thambidurai, P. and Y.-K. Park, 1988. Interactive Consistency with Multiple Failure Modes, Proc. 7th Symp. on Reliable Distributed Systems, Columbus, OH, pp. 93--100, Oct. 1988.

[20]

Therneau, T. and P. Grambsch. 2000. Modeling Survival Data: Extending the Cox Model. Springer.

[21]

Vincent, T. L. and J. L. Brown. 2005. Evolutionary Game Theory, Natural Selection and Darwinian Dynamics. Cambridge University Press. 382pp.

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Sadkhan SAyad M(2021)Game Theory Role in Wireless Network Security – Status, Challenges and Future trends2021 International Conference on Advance of Sustainable Engineering and its Application (ICASEA)10.1109/ICASEA53739.2021.9733015(230-235)Online publication date: 27-Oct-2021
https://doi.org/10.1109/ICASEA53739.2021.9733015
Zeng CWang YLiang FPeng X(2020)Pinocchio: A Blockchain-Based Algorithm for Sensor Fault Tolerance in Low Trust Environment2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW50202.2020.00077(416-425)Online publication date: May-2020
https://doi.org/10.1109/IPDPSW50202.2020.00077
Abdalzaher MSeddik KElsabrouty MMuta OFurukawa HAbdel-Rahman A(2016)Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A SurveySensors10.3390/s1607100316:7(1003)Online publication date: 29-Jun-2016
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cover image ACM Conferences

MSWiM '08: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems

October 2008

430 pages

ISBN:9781605582351

DOI:10.1145/1454503

General Chairs:
Sotiris Nikoketseas
CTI/University of Patras, Greece
,
Nael Abu-Ghazaleh
SUNY at Binghamton, USA
,
Program Chairs:
Brahim Bensaou
University of Science and Technology, Hong Kong
,
Violet R. Syrotiuk
Arizona State University, USA

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 27 October 2008

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MSWiM '08: The 11th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 27 - 31, 2008

British Columbia, Vancouver, Canada

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Overall Acceptance Rate 398 of 1,577 submissions, 25%

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Cited By

Sadkhan SAyad M(2021)Game Theory Role in Wireless Network Security – Status, Challenges and Future trends2021 International Conference on Advance of Sustainable Engineering and its Application (ICASEA)10.1109/ICASEA53739.2021.9733015(230-235)Online publication date: 27-Oct-2021
https://doi.org/10.1109/ICASEA53739.2021.9733015
Zeng CWang YLiang FPeng X(2020)Pinocchio: A Blockchain-Based Algorithm for Sensor Fault Tolerance in Low Trust Environment2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW50202.2020.00077(416-425)Online publication date: May-2020
https://doi.org/10.1109/IPDPSW50202.2020.00077
Abdalzaher MSeddik KElsabrouty MMuta OFurukawa HAbdel-Rahman A(2016)Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A SurveySensors10.3390/s1607100316:7(1003)Online publication date: 29-Jun-2016
https://doi.org/10.3390/s16071003
Lv YHuangfu WZhang Z(2015)The Bimodal Probability Density Distribution of the Survivability for Wireless Sensor Networks under Random Failures2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom)10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.61(284-291)Online publication date: Aug-2015
https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.61
Ma Z(2015)Towards computational models of animal communications, an introduction for computer scientistsCognitive Systems Research10.1016/j.cogsys.2014.08.00233:C(70-99)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1016/j.cogsys.2014.08.002
Ma Z(2015)Towards computational models of animal cognition, an introduction for computer scientistsCognitive Systems Research10.1016/j.cogsys.2014.08.00133:C(42-69)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1016/j.cogsys.2014.08.001
Jin YZhou XBai ZMa WXu LWu ZOoi SLiu Y(2014)Survivability-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor NetworksInternational Journal of Distributed Sensor Networks10.1155/2014/27862910:4(278629)Online publication date: Jan-2014
https://doi.org/10.1155/2014/278629
Shi HWang WKwok NChen S(2012)Game Theory for Wireless Sensor Networks: A SurveySensors10.3390/s12070905512:7(9055-9097)Online publication date: 2-Jul-2012
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(2012)Modular Methods for Verification and Validation of Air Traffic Control AlgorithmsInfotech@Aerospace 201210.2514/6.2012-2470Online publication date: 6-Sep-2012
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Ali ATixeuil SSyrotiuk VAlagöz FBensaou BAkan Ö(2010)Advanced faults patterns for WSN dependability benchmarkingProceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems10.1145/1868521.1868530(39-48)Online publication date: 17-Oct-2010
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