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Cluster Head Enhance Selection Using Type-II Fuzzy Logic for Multi-hop Wireless Sensor Network

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Intelligent Data Communication Technologies and Internet of Things (ICICI 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 38))

Abstract

Wireless sensor network is a remote network of spatially distributed small, lightweight sensors to observe physical and environment status by the measurement of temperature, pressure, vibration and to co-operatively pass their information via network to a base station (BS). In designing wireless sensor network routing protocol, enhancing energy efficiency and lifetime of remote sensor systems are critical issues as a large portion of the remote sensor systems work in unattended condition where accessing and observing are not easy. Low energy adaptive clustering hierarchy (LEACH) is a randomized probabilistic model which is not advisable in practice because it consider energy only to elect cluster head (CH) and it follows the single-hop communication which burdens the CH and may not scale well for bigger applications. Wireless sensor network has routing chain which is of requested grouping of the considerable number of nodes in the system framing a chain structure to convey a collected information to BS.

Clustering techniques arranges the framework activity in related way to go to the system versatility, limit energy utilization and accomplish delayed system lifetime. Orchestrate the framework activity in related way to go to the system versatility, limit energy utilization and accomplish delayed system lifetime. Most of the algorithms overburden the CH during cluster formation. An idea of fuzzy logic is come up as decision maker in applied wireless sensor network (WSN). A large portion of the algorithms use type-1 fuzzy logic (T1FL) model, but uncertain level decisions are handled by type-2 fuzzy logic (T2FL) model superior to T1FL model. The performance is analysed using NS2 simulator.

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References

  1. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of 33rd Hawaii International Conference on System Science (HICSS), Washington, DC, USA, pp. 1–10, January 2000

    Google Scholar 

  2. Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor net-works. IEEE Trans. Wirel. Commun. 1(4), 660–670 (2002)

    Article  Google Scholar 

  3. Lindsey, S., Raghabendra, C.S.: PEGASIS: power efficient gathering in sensor information systems. In: Proceedings of IEEE Aerospace Conference, pp. 3-1125–3-1130, March 2002

    Google Scholar 

  4. Gupta, I., Riordan, D., Sampalli, S.: Cluster-head election using fuzzy logic for wireless sensor networks. In: Proceeding of Communication Networks and Services Research Conference, pp. 255–260, May 2005

    Google Scholar 

  5. Kim, J.-M., Park, S.H., Han, Y.J., Chung, T.: CHEF: cluster head election mechanism using fuzzy logic in wireless sensor networks. In Proceedings of ICACT, pp. 654–659, Februray 2008

    Google Scholar 

  6. Fu, C., Jiang, Z., Wei, W., Wei, A.: An energy balanced algorithm of LEACH protocol in WSN. IJCSI Int. J. Comput. Sci 10, 354 (2012)

    Google Scholar 

  7. Taheri, H., Neamatollahi, P., Younis, O.M., Naghibzadeh, S., Yaghmaee, M.H.: An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic. Ad Hoc Netw. 10(7), 1469–1481 (2012)

    Article  Google Scholar 

  8. Sharma, T., Kumar, B.: F-MCHEL: fuzzy based master cluster head election leach protocol in wireless sensor network. Int. J. Comput. Sci. Telecommun. 3(10), 8–13 (2012)

    Google Scholar 

  9. Siew, Z.W., Liau, C.F., Kiring, A., Arifianto, M.S., Teo, K.T.K.: Fuzzy logic based cluster head election for wireless sensor network. In: Proceedings of 3rd CUTSE International Conference, Miri, Malaysia, pp. 301–306 November 2011

    Google Scholar 

  10. Nehra, V., Pal, R., Sharma, A.K.: Fuzzy based leader selection for topology controlled PEGASIS protocol for lifetime enhancement in wireless sensor network. Int. J. Comput. Technol. 4(3), 755–764 (2013)

    Article  Google Scholar 

  11. Ran, G., Zhang, H., Gong, S.: Improving on LEACH protocol of wireless sensor networks using fuzzy logic. J. Inf. Comput. Sci. 7(3), 767–775 (2010)

    Google Scholar 

  12. Ando, H., Barolli, L., Durresi, A., Xhafa, F., Koyama, A.: An intelligent fuzzy-based cluster head selection system for WSNs and its performance evaluation for D3N parameter. In: Proceedings of International Conference on Broadband, Wireless Computing, Communication and Applications, pp. 648–653, November 2010

    Google Scholar 

  13. Arabi, Z.: HERF: a hybrid energy efficient routing using a fuzzy method in wireless sensor networks. In: Proceedings International Conference on Intelligent and Advanced Systems (ICIAS), June 2010

    Google Scholar 

  14. Mamdani, E.H., Assilian, S.: Implementation of mamdani fuzzy method in employee promotion system. In: IOP Conference 2017

    Google Scholar 

  15. Dasgupta, S., Dutta, P.: An improved leach approach for head selection stratergy in a fuzzy-c means induced clustering of a WIN, 16 December 2010

    Google Scholar 

  16. Nayak, P., Anurag, D., Bhargavi, V.V.N.A.: Fuzzy based method super cluster head election for wireless sensor network with mobile base station (FM-SCHM). In: Proceedings of 2nd International Conference on Advanced Computation, Hyderabad, India, pp. 422–427 (2013)

    Google Scholar 

  17. Wang, Y.-C., Wu, F.J., Tseng, Y.C.: Mobility management algorithms and applications for mobile sensor networks. Wirel. Commun. Mobile Comput. 12(1), 7–21 (2012)

    Article  Google Scholar 

  18. Handy, M.J., Haase, M., Timmermann, D.: Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In: Proceedings of International Workshop Mobile Wireless Communication Networks, pp. 368–372, September 2002

    Google Scholar 

  19. Nayak, P., Anurag, D.: A fuzzy logic-based clustering algorithm for WSNto extend the network lifetime. IEEE Sensor J. 16(1), 137–144 (2016)

    Article  Google Scholar 

  20. Kocakulak, M., Butun, I.: An overview of WSNs towards internet of things. In: IEEE 7th Annual Computing Workshop and Conference (2017)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication, UBDT College of Engineering, Davangere, India

    K. M. Ramya & S. N. Hanumanthappa

Authors
  1. K. M. Ramya
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  2. S. N. Hanumanthappa
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Corresponding author

Correspondence to K. M. Ramya .

Editor information

Editors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, India

    D. Jude Hemanth

  2. Department of Electronics and Computer Engineering, Tribhuvan University, Kirtipur, Nepal

    Subarna Shakya

  3. School of Science, Edith Cowan University, Joondalup Campus, Joondalup, WA, Australia

    Zubair Baig

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Ramya, K.M., Hanumanthappa, S.N. (2020). Cluster Head Enhance Selection Using Type-II Fuzzy Logic for Multi-hop Wireless Sensor Network. In: Hemanth, D., Shakya, S., Baig, Z. (eds) Intelligent Data Communication Technologies and Internet of Things. ICICI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-030-34080-3_2

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