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InterCriteria Analysis of Different Variants of ACO Algorithm for Wireless Sensor Network Positioning

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11189))

Abstract

Wireless sensor networks are formed by spatially distributed sensors, which communicate in a wireless way. This network can monitor various kinds of environment and physical conditions like movement, noise, light, humidity, images, chemical substances etc. A given area needs to be fully covered with minimal number of sensors and the energy consumption of the network needs to be minimal too. We propose several algorithms, based on Ant Colony Optimization, to solve the problem. We study the algorithms behaviour when the number of ants varies from 1 to 10. We apply InterCriteria analysis to study relations between proposed algorithms and number of ants and analyse correlation between them.

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References

  1. Atanassov, K.: Index Matrices: Towards an Augmented Matrix Calculus. Studies in Computational Intelligence, vol. 573. Springer, Basel (2014). https://doi.org/10.1007/978-3-319-10945-9

    Book  MATH  Google Scholar 

  2. Atanassov, K.: Intuitionistic Fuzzy Sets, VII ITKR Session, Sofia, 20–23 June 1983 (1983). Reprinted: Int J Bioautomation, 20(S1), 2016, S1–S6

    Article  MathSciNet  Google Scholar 

  3. Atanassov, K.: Review and New Results on Intuitionistic Fuzzy Sets, Mathematical Foundations of Artificial Intelligence Seminar, Sofia (1988). Preprint IM-MFAIS-1-88, Reprinted: Int J Bioautomation, 20(S1), 2016, S7–S16

    Article  MathSciNet  Google Scholar 

  4. Atanassov, K., Atanassova, V., Gluhchev, G.: InterCriteria analysis: ideas and problems. Notes Intuitionistic Fuzzy Sets 21(2), 81–88 (2015)

    MATH  Google Scholar 

  5. Atanassov, K., Mavrov, D., Atanassova, V.: Intercriteria decision making: a new approach for multicriteria decision making based on index matrices and intuitionistic fuzzy sets. Issues IFSs GNs 11, 1–8 (2014)

    Google Scholar 

  6. Atanassov, K., Szmidt, E., Kacprzyk, J.: On intuitionistic fuzzy pairs. Notes Intuitionistic Fuzzy Sets 19(3), 1–13 (2013)

    Article  Google Scholar 

  7. Fidanova, S., Marinov, P., Alba, E.: Ant algorithm for optimal sensor deployment. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds.) Computational Intelligence, Studies of Computational Intelligence, vol. 399, pp. 21–29. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-27534-0_2

    Chapter  Google Scholar 

  8. Fidanova, S., Marinov, P., Paprzycki, M.: Influence of the number of ants on multi-objective ant colony optimization algorithm for wireless sensor network layout. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2013. LNCS, vol. 8353, pp. 232–239. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-43880-0_25

    Chapter  Google Scholar 

  9. Fidanova, S., Marinov, P., Paprzycki, M.: Influence of the number of ants on multi-objective ant colony optimization algorithm for wireless sensor network layout. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2013. LNCS, vol. 8353, pp. 232–239. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-43880-0_25

    Chapter  Google Scholar 

  10. Fidanova, S., Shindarov, M., Marinov, P.: Wireless sensor positioning using ACO algorithm. In: Sgurev, V., Yager, R.R., Kacprzyk, J., Atanassov, K.T. (eds.) Recent Contributions in Intelligent Systems. SCI, vol. 657, pp. 33–44. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-41438-6_3

    Chapter  Google Scholar 

  11. Fidanova, S., Roeva, O., Paprzycki, M., Gepner, P.: InterCriteria analysis of ACO start startegies. In: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, pp. 547–550 (2016)

    Google Scholar 

  12. Hernandez, H., Blum, C.: Minimum energy broadcasting in wireless sensor networks: an ant colony optimization approach for a realistic antenna model. J. Appl. Soft Comput. 11(8), 5684–5694 (2011)

    Article  Google Scholar 

  13. Ikonomov, N., Vassilev, P., Roeva, O.: ICrAData - software for InterCriteria analysis. Int. J. Bioautomation 22(1), 1–10 (2018)

    Article  Google Scholar 

  14. Jourdan, D.B.: Wireless sensor network planning with application to UWB localization in GPS-denied environments, Massachusets Institute of Technology, Ph.D. thesis (2000)

    Google Scholar 

  15. Konstantinidis, A., Yang, K., Zhang, Q., Zainalipour-Yazti, D.: A multiobjective evolutionary algorithm for the deployment and power assignment problem in wireless sensor networks. J. Comput. Netw. 54(6), 960–976 (2010)

    Article  Google Scholar 

  16. Molina, G., Alba, E., Talbi, E.G.: Optimal sensor network layout using multi-objective Metaheuristics. Univers. Comput. Sci. 14(15), 2549–2565 (2008)

    Google Scholar 

  17. Pottie, G.J., Kaiser, W.J.: Embedding the internet: wireless integrated network sensors. Commun. ACM 43(5), 51–58 (2000)

    Article  Google Scholar 

  18. Krawczak, M., Bureva, V., Sotirova, E., Szmidt, E.: Application of the InterCriteria decision making method to universities ranking. In: Atanassov, K.T., et al. (eds.) Novel Developments in Uncertainty Representation and Processing. AISC, vol. 401, pp. 365–372. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26211-6_31

    Chapter  Google Scholar 

  19. Todinova, S., Mavrov, D., Krumova, S., Marinov, P., Atanassova, V., Atanassov, K., Taneva, S.G.: Blood plasma thermograms dataset analysis by means of InterCriteria and correlation analyses for the case of colorectal cancer. Int. J. Bioautomation 20(1), 115–124 (2016)

    Google Scholar 

  20. Wolf, S., Merz, P.: Evolutionary local search for the minimum energy broadcast problem. In: van Hemert, J., Cotta, C. (eds.) EvoCOP 2008. LNCS, vol. 4972, pp. 61–72. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78604-7_6

    Chapter  Google Scholar 

  21. Xu, Y., Heidemann, J., Estrin, D.: Geography informed energy conservation for ad hoc routing. In: Proceedings of the 7th ACM/IEEE Annual International Conference on Mobile Computing and Networking, Italy, pp. 70–84 (2001)

    Google Scholar 

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Acknowledgments

Work presented here is partially supported by the Bulgarian National Scientific Fund under Grants DFNI DN 12/5 “Efficient Stochastic Methods and Algorithms for Large-Scale Problems” and DN 02/10“New Instruments for Knowledge Discovery from Data, and their Modelling”.

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Correspondence to Stefka Fidanova .

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Fidanova, S., Roeva, O. (2019). InterCriteria Analysis of Different Variants of ACO Algorithm for Wireless Sensor Network Positioning. In: Nikolov, G., Kolkovska, N., Georgiev, K. (eds) Numerical Methods and Applications. NMA 2018. Lecture Notes in Computer Science(), vol 11189. Springer, Cham. https://doi.org/10.1007/978-3-030-10692-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-10692-8_10

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