Energy Efficient Secure Cluster Head Selection in Clustering for Internet of Things by using Nature Inspired Computing (NIC) Techniques

Authors

  • Voore Subba Rao  Department of CSE, Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India
  • Dr. S. K. Tyagi  Department of CSE, Chaudhary Charan Singh University, Meerut, Uttar Pradesh, India

Keywords:

Optimization, Biogeography Based Optimization, Cluster Head, Wireless Sensor Network, Internet of Things (IoT).

Abstract

Internet of Things(IoT) is a promising technologies to connect virtually various objects to the Internet through sensors. All these virtually connected objects connect, monitor and collected the information by sensors and finally processed these information in internet that is visible by the end user. The terminology ‘Things’ are the smart devices are grouped as clusters for energy efficient routing are organized by clustering algorithms in the wireless sensor network for IoT context. But their applications are efficiently enhance challenges in Internet of Things(IoT). The energy efficient and secure cluster head selection optimization by newly nature inspired computing algorithms i.e. Biogeography-Based Optimization(BBO) for solving optimization problems. The cluster head selection plays a prominent role to enhance network life time by transferring data packets to the base station in IoT concept. In the proposed paper, the selection of secure cluster head optimized by Biogeography Based Optimization(BBO) to improve the energy based sensor nodes, network lifetime, stable and secure network and quality of network better simulation results by MATLAB are compared with Stable Election Protocol(SEP), Evolutionary Routing Protocol(ERP), Intelligent Hierarchical Clustering Routing Protocol(IHCR).

References

  1. Atzori, Luigi, Antonio Iera, and Giacomo Morabito. "The internet of things: A survey." Computer networks 54.15 (2010): 2787-2805.
  2. D Wei, H Anthony Chan, “Clustering Ad Hoc Networks:Schemes and Classi?cations,” IEEE, 2006.
  3. K. Akkaya, M. Younis, “A survey on routing protocols for wireless sensor networks,” Elsevier Journal of Ad Hoc Networks,vol. 3, no. 3, 2005, pp. 325-349.
  4. Leu, Jenq-Shiou, et al. "Energy efficient clustering scheme for prolonging the lifetime of wireless sensor network with isolated nodes." IEEE communications letters 19.2 (2014): 259-262.
  5. M. Younis, M. Youssef, K. Arisha, “Energy-aware manage-ment in cluster-based sensor networks,” Computer Networks,vol. 43, no. 5, 2003, pp. 649-668.
  6. Y.T. Hou, Y. Shi, H.D. Sherali, “On energy provisioning and relay node placement for wireless sensor networks,” IEEE Transactions on Wireless Communications, vol. 4, no. 5, 2005,pp. 2579-2590.
  7. K. Dasgupta, K. Kalpakis, P. Namjoshi, “An ef?cient clustering based heuristic for data gathering and aggregation in sensor networks,” in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC, 2003), New Orleans,LA, March 2003.
  8. Agarwal PK, Procopiuc CM (2002) Exact and approximation algorithms for clustering. Algorithmica 33(2):201–226
  9. Dorigo M, Birattari M, Stutzle T(2006)Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39.
  10. Song M, Cheng-Lin Z (2011) Unequal clustering algorithm for WSN based on fuzzy logic and improved ACO. J China Univ Posts Tele-communications 18:89–97.
  11. Bhari A, Wazed S, jaekal A, Bandyopadhyay S(2009) A genetic algorithm based approach for energy ef?cient routing in two-tiered sensor networks. Ad-Hoc Netw 7:665–676
  12. Yu H, Xiaohui W (2011) PSO-based energy-balanced double cluster head clustering routing for wireless sensor networks. Proc Eng 15:3073–3077.
  13. D. Simon, “Biogeography-based optimization,” IEEE Transactions on Evolutionary Computation, vol. 12, pp. 702–713, 2008.
  14. Chatterjee A, Siarry P, Nakib A, Blanc R(2012) An improved biogeography based optimization approach for segmentation of human head CT-scan images employing fuzzy entropy. Eng Appl Artif Intell 25:1698–1709.
  15. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-ef?cient communication protocol for wireless microsensor networks,” in in Proc. of International Conference on System sciences, 2000.
  16. G. Smaragdakis, I. Matta, A. Bestavros et al., “Sep: A stable election protocol for clustered heterogeneous wireless sensor networks,” in in Proc. of International workshop on sensor and actor network protocols and applications, 2004.
  17. A. A. Baraa and E. A. Khalil, “A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks,” Applied Soft Computing, vol. 12, pp. 1950–1957, 2012.
  18. A. W. Matin and S. Hussain, “Intelligent hierarchical cluster-based routing,” life, vol. 7, p. 8, 2006.
  19. Nam, Choon-Sung, Hee-Jin Jeong, and Dong-Ryeol Shin. "The adaptive cluster head selection in wireless sensor networks." 2008 IEEE International Workshop on Semantic Computing and Applications. IEEE, 2008.
  20. Rajesh Patel, Sunil Pariyani, Vijay Ukani,” Energy and throughput Analysis of Hierarchical Routing Protocol(LEACH) for Wireless Sensor Networks”, International Journal of Computer Applications Volume 20- No. 4 (April 2011).
  21. Yuh Ren Tsai, “Coverage Preserving Routing Protocols for Randomly Distributed Wireless Sensor Networks”, IEEE Transactions on Wireless Communications, Volume 6- No. 4 (April 2007).
  22. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-ef?cient communication protocol for wireless microsensor networks,” in in Proc. of International Conference on System sciences, 2000.
  23. G. Smaragdakis, I. Matta, A. Bestavros et al., “Sep: A stable election protocol for clustered heterogeneous wireless sensor networks,” in in Proc. of International workshop on sensor and actor network protocols and applications, 2004.
  24. A.W. Matin and S. Hussain, “Intelligent hierarchical cluster-based routing,” life, vol. 7, p. 8, 2006.
  25. A. A. Baraa and E. A. Khalil, “A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks,” Applied Soft Computing, vol. 12, pp. 1950–1957, 2012.
  26. A. W. Matin and S. Hussain, “Intelligent hierarchical cluster-based routing,” life, vol. 7, p. 8, 2006.
  27. Mao S, Zhao C, Zhou Z, Ye Y (2013) An improved fuzzy unequal clustering algorithm for wireless sensor network. MobNetwAppl 18:206–214.
  28. Glover F., (1986). Future paths for integer programming and links to artficial intelligence, Computers and Operations Research,13,533-549 (1986).
  29. Blum, C. and Roli, A., 2003. `Metaheuristics in combinatorial optimization: Overview and conceptual comparison', ACM Comput. Surv., 35, 268-308.
  30. Mao S, Zhao C, Zhou Z, Ye Y (2013) An improved fuzzy unequal clustering algorithm for wireless sensor network. MobNetwAppl 18:206–214.
  31. Yu H, Xiaohui W (2011) PSO-based energy-balanced double clusterhead clustering routing for wireless sensor networks. Proc Eng 15:3073–3077.
  32. Rarick R, Simon D, Villaseca F, Vyakaranam B (2009) Biogeographybased optimization and the solution of the power ?ow problem. In: Proceedings of the IEEE conference on systems, man, and cybernetics. San Antonio, pp 1029–1034.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2014-12-30

Issue

Volume 1, Issue 1, -2014

Section

Research Articles

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How to Cite

[1]
Voore Subba Rao, Dr. S. K. Tyagi, " Energy Efficient Secure Cluster Head Selection in Clustering for Internet of Things by using Nature Inspired Computing (NIC) Techniques , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.239-247, -2014.