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A Novel Hybrid Voter Using Genetic Algorithm and Performance History
AKHILESH PATHAK, Anand Mohan
Pages - 117 - 125     |    Revised - 01-07-2011     |    Published - 05-08-2011
Published in International Journal of Artificial Intelligence and Expert Systems (IJAE)
Volume - 2   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
MORE INFORMATION
References   |   Cited By (3)   |   Abstracting & Indexing
KEYWORDS
TMR, Soft threshold, Genetic Algorithm, Weighted Average Voting
ABSTRACT
Triple Modular Redundancy (TMR) is generally used to increase the reliability of real time systems where three similar modules are used in parallel and the final output is arrived at using voting methods. Numerous majority voting techniques have been proposed in literature however their performances are compromised for some typical set of module output value. Here we propose a new voting scheme for analog systems retaining the advantages of previous reported schemes and reduce the disadvantages associated with them. The scheme utilizes a genetic algorithm and previous performances history of the modules to calculate the final output. The scheme has been simulated using MATLAB and the performance of the voter has been compared with that of fuzzy voter proposed by Shabgahi et al [4]. The performance of the voter proposed here is better than the existing voters.
CITED BY (3)  
1 Pathak, A., Agarwal, T., & Mohan, A. (2015). A Novel Fuzzy Membership Partitioning for Improved Voting in Fault Tolerant System. Journal of Intelligent Learning Systems and Applications, 7(01), 1.
2 Mirsaeidi, M., & Karimi, A. (2015). A novel probabilistic bit voter using genetic algorithm for fault-tolerant systems. International Journal of Computer Science Issues (IJCSI), 12(4), 88.
3 Latifi, Z., & Karimi, A. (2014). A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot. Procedia Computer Science, 42, 301-307.
ABSTRACTING & INDEXING
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
REFERENCES
Behrooz Parhami, "Optimal Algorithm for Exact, Inexact and Approval voting", FTCS- 22: Twenty second International symposium on fault tolerant computing, Boston, July 1992, pp. 404-411.
Behrooz Parhami, "Voting algorithms", IEEE Trans. Reliability, Vol. 43, No. 4, pp. 617-629,December 1994.
Darrel Whitley, “A genetic algorithm tutorial”, Statistics and Computing (1994) 4, 65-85.
David E. Goldberg, “Genetic Algorithms in Search, Optimization & Machine Learning”, AddisonWesley Publications, ISBN : 981-405-394-5.
G. Latif-Shabgahi, A.J. Hirst, “A Fuzzy Voting Scheme for Hardware and Software Fault Tolerant Systems”, Fuzzy Sets and Systems 150 (2005) 579–598, Elsevier Publication.
G. Latif-Shabgahi, J. M. Bass, S. Bennett, “History-based weighted average voter: a novel software voting algorithm for fault-tolerant computer systems,” in 9th workshop Parallel and Distributed Processing, 2001, pp. 402-409
John H Holland, “Genetic Algorithms”, Internet:http://www2.econ.iastate.edu/tesfatsi/holland.gaintro.htm.
M.D. Krstic, M.K. Stojcev G. Lj. Djordjevic and I.D. Andrejic," A mid-value select voter",Microelectronics Reliability, Volume 45, Issues 3-4, March-April 2005, Pages 733-738, Elsevier Publication.
Milos Manic, Deborah Frincke, "Towards the Fault Tolerant Software: Fuzzy Extension of Crisp Equivalence Voters", IECON’01: The 27th Annual conference of the IEEE Industrial electronics Society, 2001.
Parag K. Lala, “Fault Tolerant and Fault Testable Hardware Design”, BS Publications, ISBN: 81-7800-038-5.
Von Neumann, J., “Probabilistic logics and synthesis of reliable organisms from unreliable components”, Automata Studies, in Annals of Mathematical Studies, No. 34, 43-98(ED.: C. E.Shannon and J. McCarthy), Princeton University Press (1956).
MANUSCRIPT AUTHORS
Mr. AKHILESH PATHAK
CEMILAC - India
pathak.akhilesh@gmail.com
Professor Anand Mohan
Department of Electronics Engineering - India


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