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A bio inspired and trust based approach for clustering in WSN

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Abstract

Wireless sensor network (WSN) is a special kind of ad-hoc network consists of battery powered low cost sensor nodes with limited computation and communication capabilities deployed densely in a target area. Clustering in WSN plays an important role because of its inherent energy saving capability and suitability for highly scalable network. This paper is an extended version of our previous work (Sahoo et al. 2013a). Although the clustering strategy presented in this paper is same as our previous work but here a light weight dynamic TRUST model along with honey bee mating algorithm is presented, which will only prevent malicious node to be a cluster head. The choice of light weight TRUST model makes our clustering method more secure and energy efficient, which are most pivotal issues for resource constrained sensor network. We have also introduced a priority scheme among the trust metrics which is more realistic. Furthermore, the use of honey bee mating algorithm finds most appropriate node as cluster head. Simulation results are also presented here to compare the performance of our algorithm with low energy adaptive clustering hierarchy and advertisement time-out driven bee mating approach to maintain fair energy level in sensor networks.

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References

  • Abbass HA (2001a) A monogenous MBO approach to satisfiability. In: Proceedings of international conference on computational intelligence for modeling, control and automation, Las Vegas, NV, USA

  • Abbass HA (2001b) Marriage in honey-bee optimization (MBO): a haplometrosis polygynous swarming approach. In: The congress on evolutionary computation, Seoul, Korea, pp 207–214

  • Afshar A, Haddada OB, Marino MA, Adams BJ (2007a) Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. J Frankl Inst 344:452–462

    Article  MATH  Google Scholar 

  • Afshar A, Hadded OB, Marino MA, Adams BJ (2007b) Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. In: Journal of the Franklin Institute, proceedings of the 2001 congress on evolutionary computation, vol 1, pp 452-462

  • Bao F, Chen I, Chang M, Cho J (2012) Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection. IEEE Trans Netw Serv Manag 9(2):169–183

    Article  Google Scholar 

  • Crosby GV, Pissinou N, Gadze J (2006a) A framework for trust-based cluster head election in wireless sensor networks. In: Proceedings of second IEEE workshop on dependability and security in sensor networks and systems

  • Crosby GV, Pissinou N, Gadze J (2006b) A framework for trust-based cluster head election in wireless sensor networks. In: Proceedings of second IEEE workshop on dependability and security in sensor networks and systems, pp 10–22

  • de Castro LD, Timmis J (2002) Artificial immune systems: a new computational intelligence approach. Springer, Heidelberg

    MATH  Google Scholar 

  • Dorigo M, Stutzle T (2004) Ant colony optimization. A Bradford book. The MIT Press Cambridge, Massachusetts, London, England

    MATH  Google Scholar 

  • Fathian M, Amiri B, Maroosi A (2007) Application of honey bee mating optimization algorithm on clustering. Appl Math Comput. doi:10.1016/j.amc.2007.02.029

  • Ferdous R, Muthukkumarasamy V, Sithirasenan E (2011) Trust-based cluster head selection algorithm for mobile ad hoc networks. In: Proceedings of international joint conference on IEEE TrustCom-1111/IEEE ICESS-11/FCST-11, pp 589–596

  • Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless micro sensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  • Hur J, Lee Y, Yoon H, Choi D, Jin S (2005) Trust evaluation model for wireless sensor networks. In: The 7th international conference on advanced communication technology, Gangwon-Do, Korea

  • Kumar D, Aseri TC, Patel RB (2009) EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput Commun 32(4):662–667

    Article  Google Scholar 

  • Li X, Zhou F, Junping D (2013) LDTS: a lightweight and dependable trust system for clustered wireless sensor networks. IEEE Trans Inform Forensic Secur 8(6):924–935

    Article  Google Scholar 

  • Manjeshwar A, Agrawal DP (2001) TEEN: a protocol for enhanced efficiency in wireless sensor networks. In: Proceedings of international workshop on parallel and distributed computing issues in wireless networks and mobile computing, San Francisco, CA, April

  • Manjeshwar A, Agrawal DP (2002) APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In: Proceedings of international parallel and distributed processing symposium

  • Marinakis Y, Marinaki M, Matsatsinis N (2007) A hybrid clustering algorithm based on honey bees mating optimization and greedy randomized adaptive search procedure. In: Proceedings of second international conference, LION 2007 II, Trento, Italy, December 8–12

  • Momani M (2008) Bayesian methods for modeling and management of trust in wireless sensor networks. Ph.D Thesis, University of Technology, Sydney, July

  • Momani M, Challa S (2010) Survey of trust models in different network domains. Int J Ad Hoc Sensor Ubiquitous Comput 1(3):1–19

    Article  Google Scholar 

  • Sahoo RR, Sardar AR, Singh M, Ray S, Kumar S (2013a) Trust based secure and energy efficient clustering in wireless sensor network: a bee mating approach. In: PReMI 2013, LNCS 8251, Springer, Berlin, Heidelberg, pp 100–107

  • Sahoo RR, Singh M, Sahoo BM, Majumder K, Ray S, Sarkar SK (2013b) A lightweight trust based secure and energy efficient clustering in wireless sensor network: honey bee mating intelligence approach. In: Proceedings of international conference on computational intelligence: modeling techniques and applications, procedia technology, Elsevier, pp 27–28

  • Saleem M, Khayam SA, Farooq M (2008) Formal modeling of bee adhoc: a bio-inspired mobile ad hoc network routing protocol. In: Proceedings of GECCO

  • Senthilkumar J, Chandrasekaran M (2011) Improving the performance of wireless sensor network using bee’s mating intelligence. Eur J Sci Res 55(3):452–465

    Google Scholar 

  • Senthilkumar J, Chandrasekaran M, Suresh Y, Arumugam S, Mohanraj V (2011) Advertisement timeout driven bee’s mating approach to maintain fair energy level in sensor networks. Appl Soft Comput 11(5):4029–4035

    Article  Google Scholar 

  • Shaikh RA, Jameel H, d’Auriol BJ, Lee H, Lee S (2009) Group-based trust management scheme for clustered wireless sensor networks. IEEE Trans Parallel Distrib Syst 20(11):1698–1712

    Article  Google Scholar 

  • Wedde H, Farooq M, Pannenbaecke T, Vogel B, Mueller C, Meth J, Jeruschkat R (2005) BeeAdHoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior. In: Proceedings of GECCO

  • Younis O, Fahmy S (2004) HEED: a hybrid energy-efficient distributed clustering approach for ad-hoc sensor networks. IEEE Trans Mobile Comput 3(4):366–379

    Article  Google Scholar 

  • Zahariadis T, Leligou HC, Trakadas P, Voliotis S (2010) Trust management in wireless sensor networks. Eur Trans Telecommun 21:386–395

    Google Scholar 

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Acknowledgments

Rashmi Ranjan Sahoo thankfully acknowledges the financial support obtained from TEQIP-II programme by Ministry of Human Resource and Development, India.

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Authors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, West Bengal, India

    Rashmi Ranjan Sahoo, Sudhabindu Ray & Subir Kumar Sarkar

  2. Department of Computer Science and Engineering, NITMAS, Sarisha, West Bengal, India

    Abdur Rahaman Sardar

  3. Department of Information Technology, IEM, Kolkata , West Bengal, India

    Moutushi Singh

Authors
  1. Rashmi Ranjan Sahoo
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  2. Abdur Rahaman Sardar
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  3. Moutushi Singh
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  4. Sudhabindu Ray
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  5. Subir Kumar Sarkar
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Corresponding author

Correspondence to Rashmi Ranjan Sahoo.

Additional information

This work is partly sponsored by TEQIP-II, MHRD India.

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Sahoo, R.R., Sardar, A.R., Singh, M. et al. A bio inspired and trust based approach for clustering in WSN. Nat Comput 15, 423–434 (2016). https://doi.org/10.1007/s11047-015-9491-8

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  • DOI: https://doi.org/10.1007/s11047-015-9491-8

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