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A Fuzzy-Based System for Selection of Actor Nodes in WSANs Considering Actor Reliability and Load Distribution

  • Donald ElmaziEmail author
  • Miralda Cuka
  • Makoto Ikeda
  • Leonard Barolli
  • Makoto Takizawa
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 29)

Abstract

Wireless Sensor and Actor Network (WSAN) is formed by the collaboration of micro-sensor and actor nodes. The sensor nodes have responsibility to sense an event and send information towards an actor node. The actor node is responsible to take prompt decision and react accordingly. In order to provide effective sensing and acting, a distributed local coordination mechanism is necessary among sensors and actors. In this work, we consider the actor node selection problem and propose a fuzzy-based system (FBS) that based on data provided by sensors and actors selects an appropriate actor node. We use 4 input parameters: Number of Sensors per Actor (NSA), Distance to Event (DE), Remaining Energy (RE) and Actor Reliability (AR) as new parameter. The output parameter is Actor Selection Decision (ASD). Considering NSA parameter, the ASD has better values when NSA is medium. Thus, when the NSA value is 0.5 the load is distributed better and in this situation the possibility for the actor to be selected is high. Also, for higher values of AR, the actor is selected with high possibility.

References

  1. 1.
    Akyildiz, I.F., Kasimoglu, I.H.: Wireless sensor and actor networks: research challenges. Ad Hoc Netw. J. 2(4), 351–367 (2004)CrossRefGoogle Scholar
  2. 2.
    Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Computer Netw. 38(4), 393–422 (2002)CrossRefGoogle Scholar
  3. 3.
    Boyinbode, O., Le, H., Takizawa, M.: A survey on clustering algorithms for wireless sensor networks. Int. J. Space Based Situated Comput. 1(2/3), 130–136 (2011)CrossRefGoogle Scholar
  4. 4.
    Bahrepour, M., Meratnia, N., Poel, M., Taghikhaki, Z., Havinga, P.J.: Use of wireless sensor networks for distributed event detection in disaster managment applications. Int. J. Space Based Situated Comput. 2(1), 58–69 (2012)CrossRefGoogle Scholar
  5. 5.
    Haider, N., Imran, M., Saad, N., Zakariya, M.: Performance analysis of reactive connectivity restoration algorithms for wireless sensor and actor networks. In: IEEE Malaysia International Conference on Communications (MICC-2013), pp. 490–495, November 2013Google Scholar
  6. 6.
    Abbasi, A., Younis, M., Akkaya, K.: Movement-assisted connectivity restoration in wireless sensor and actor networks. IEEE Trans. Parallel Distrib. Syst. 20(9), 1366–1379 (2009)CrossRefGoogle Scholar
  7. 7.
    Li, X., Liang, X., Lu, R., He, S., Chen, J., Shen, X.: Toward reliable actor services in wireless sensor and actor networks. In: IEEE 8th International Conference on Mobile Adhoc and Sensor Systems (MASS), pp. 351–360, October 2011Google Scholar
  8. 8.
    Akkaya, K., Younis, M.: COLA: a coverage and latency aware actor placement for wireless sensor and actor networks. In: IEEE 64th Conference on Vehicular Technology (VTC-2006) Fall, pp. 1–5, September 2006Google Scholar
  9. 9.
    Kakarla, J., Majhi, B.: A new optimal delay and energy efficient coordination algorithm for WSAN. In: IEEE International Conference on Advanced Networks and Telecommuncations Systems (ANTS), pp. 1–6, December 2013Google Scholar
  10. 10.
    Elmazi, D., Cuka, M., Ikeda, M., Barolli, L.: A fuzzy-based system for actor node selection in WSANs for improving network connectivity and increasing number of covered sensors. In: The 21st International Conference on Network-Based Information Systems (NBiS-2018) (2018)Google Scholar
  11. 11.
    Akbas, M., Turgut, D.: APAWSAN: actor positioning for aerial wireless sensor and actor networks. In: IEEE 36th Conference on Local Computer Networks (LCN), pp. 563–570, October 2011Google Scholar
  12. 12.
    Akbas, M., Brust, M., Turgut, D.: Local positioning for environmental monitoring in wireless sensor and actor networks. In: IEEE 35th Conference on Local Computer Networks (LCN), pp. 806–813, October 2010Google Scholar
  13. 13.
    Melodia, T., Pompili, D., Gungor, V., AkyildizZX, I.: Communication and coordination in wireless sensor and actor networks. IEEE Trans. Mob. Comput. 6(10), 1126–1129 (2007)CrossRefGoogle Scholar
  14. 14.
    Gungor, V., Akan, O., Akyildiz, I.: A real-time and reliable transport (RT) 2 protocol for wireless sensor and actor networks. IEEE/ACM Trans. Networking 16(2), 359–370 (2008)CrossRefGoogle Scholar
  15. 15.
    Selvaradjou, K., Handigol, N., Franklin, A., Murthy, C.: Energy-efficient directional routing between partitioned actors in wireless sensor and actor networks. IET Commun. 4(1), 102–115 (2010)CrossRefGoogle Scholar
  16. 16.
    Nakayama, H., Fadlullah, Z., Ansari, N., Kato, N.: A novel scheme for WSAN sink mobility based on clustering and set packing techniques. IEEE Trans. Autom. Control 56(10), 2381–2389 (2011)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Inaba, T., Sakamoto, S., Kolici, V., Mino, G., Barolli, L.: A CAC scheme based on fuzzy logic for cellular networks considering security and priority parameters. In: The 9th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA-2014), pp. 340–346 (2014)Google Scholar
  18. 18.
    Spaho, E., Sakamoto, S., Barolli, L., Xhafa, F., Barolli, V., Iwashige, J.: A fuzzy-based system for peer reliability in JXTA-overlay P2P considering number of interactions. In: The 16th International Conference on Network-Based Information Systems (NBiS-2013), pp. 156–161 (2013)Google Scholar
  19. 19.
    Matsuo, K., Elmazi, D., Liu, Y., Sakamoto, S., Mino, G., Barolli, L.: FACS-MP: a fuzzy admission control system with many priorities for wireless cellular networks and its performance evaluation. J. High Speed Netw. 21(1), 1–14 (2015)CrossRefGoogle Scholar
  20. 20.
    Grabisch, M.: The application of fuzzy integrals in multicriteria decision making. Eur. J. Oper. Res. 89(3), 445–456 (1996)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Inaba, T., Elmazi, D., Liu, Y., Sakamoto, S., Barolli, L., Uchida, K.: Integrating wireless cellular and ad-hoc networks using fuzzy logic considering node mobility and security. In: The 29th IEEE International Conference on Advanced Information Networking and Applications Workshops (WAINA-2015), pp. 54–60 (2015)Google Scholar
  22. 22.
    Kulla, E., Mino, G., Sakamoto, S., Ikeda, M., Caballé, S., Barolli, L.: FBMIS: a fuzzy-based multi-interface system for cellular and ad hoc networks. In: International Conference on Advanced Information Networking and Applications (AINA-2014), pp. 180–185 (2014)Google Scholar
  23. 23.
    Elmazi, D., Kulla, E., Oda, T., Spaho, E., Sakamoto, S., Barolli, L.: A comparison study of two fuzzy-based systems for selection of actor node in wireless sensor actor networks. J. Ambient Intell. Humanized Comput. 6(5), 635–645 (2015)CrossRefGoogle Scholar
  24. 24.
    Zadeh, L.: Fuzzy logic, neural networks, and soft computing. Commun. ACM 37, 77–84 (1994)CrossRefGoogle Scholar
  25. 25.
    Spaho, E., Sakamoto, S., Barolli, L., Xhafa, F., Ikeda, M.: Trustworthiness in P2P: performance behaviour of two fuzzy-based systems for JXTA-overlay platform. Soft Comput. 18(9), 1783–1793 (2014)CrossRefGoogle Scholar
  26. 26.
    Inaba, T., Sakamoto, S., Kulla, E., Caballe, S., Ikeda, M., Barolli, L.: An integrated system for wireless cellular and ad-hoc networks using fuzzy logic. In: International Conference on Intelligent Networking and Collaborative Systems (INCoS-2014), pp. 157–162 (2014)Google Scholar
  27. 27.
    Matsuo, K., Elmazi, D., Liu, Y., Sakamoto, S., Barolli, L.: A multi-modal simulation system for wireless sensor networks: a comparison study considering stationary and mobile sink and event. J. Ambient Intell. Humanized Comput. 6(4), 519–529 (2015)CrossRefGoogle Scholar
  28. 28.
    Kolici, V., Inaba, T., Lala, A., Mino, G., Sakamoto, S., Barolli, L.: A fuzzy-based CAC scheme for cellular networks considering security. In: International Conference on Network-Based Information Systems (NBiS-2014), pp. 368–373 (2014)Google Scholar
  29. 29.
    Liu, Y., Sakamoto, S., Matsuo, K., Ikeda, M., Barolli, L., Xhafa, F.: A comparison study for two fuzzy-based systems: improving reliability and security of JXTA-overlay P2P platform. Soft Comput. 20(7), 2677–2687 (2015)CrossRefGoogle Scholar
  30. 30.
    Matsuo, K., Elmazi, D., Liu, Y., Sakamoto, S., Mino, G., Barolli, L.: FACS-MP: a fuzzy admission control system with many priorities for wireless cellular networks and its perforemance evaluation. J. High Speed Netw. 21(1), 1–14 (2015)CrossRefGoogle Scholar
  31. 31.
    Mendel, J.M.: Fuzzy logic systems for engineering: a tutorial. Proc. IEEE 83(3), 345–377 (1995)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Donald Elmazi
    • 1
    Email author
  • Miralda Cuka
    • 2
  • Makoto Ikeda
    • 1
  • Leonard Barolli
    • 1
  • Makoto Takizawa
    • 3
  1. 1.Department of Information and Communication EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan
  2. 2.Graduate School of EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan
  3. 3.Department of Advanced SciencesHosei UniversityTokyoJapan

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