A Hierarchy Topology Design Using a Hybrid Evolutionary Algorithm in Wireless Sensor Networks

Author

Department of Computer Engineering & IT, Payam Noor University (PNU), Tehran, Iran

Abstract

Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of cluster heads are two important issues. Many routing protocols are introduced to discover the optimal routes in order to remove intermediate nodes to reduce the sensors energy consumption. Therefore, for energy consumption optimization in a network, routing protocols and clustering techniques along with composition and aggregation of data are provided. In this paper, to design a hierarchy topology, a hybrid evolutionary approach, a combination of genetic and imperialist competition algorithms is applied. First, the genetic algorithm is applied to achieve an optimal clusters number where all effective network parameters are taken in into account. Aftermath, the optimal positions of cluster heads inside every cluster are calculated utilizing the imperialist approach. Our results show a significant increment in the network lifetime, lower data-packet lost, higher robust routing compared with standard LEACH and the ICA based LEACH.

Keywords


  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E., “Wireless sensor networks: a survey”, Journal of Computer Networks, Vol. 38 (2002), 393–422.
  2. Arampatzis, T., Lygeros, J., Manesis, S., “A survey of applications of wireless sensors and wireless sensor networks”, the 2005 IEEE International Symposium on Mediterrean Conference on Control and Automation 2005, 719-724.
  3. Sharma, S., Kumar, R., Machine, B., “Issues and Challenges in Wireless Sensor Networks”, International Conference on Intelligence and Research Advancement (ICMIRA) 2013, India.
  4.  Anastasi, G., Conti, M., Di Francesco, M., Passarella, A., “Energy conservation in wireless sensor networks: A survey,” Journal of Ad-Hoc networks, Vol. 7 (2009), 537-568.
  5. Dargie, W., Poellabauer, C., “Fundamentals of Wireless Sensor Networks: Theory and Practice”, Wiley Black well (2010).
  6.  C. Zhua, C. Zhenga, L.Shuc, G. Hana, "A survey on coverage and connectivity issues in wireless sensor networks", Journal of Network and Computer Applications, Vol. 35 (2012), 619–632.
  7. N. Enami, N. M. Charkari, and K. D. Ahmadi, “Intelligent clustering for balanced energy consumption in wireless sensor networks”, Journal of International Journal Advanced Computer Technology, Vol. 3, No. 2 (2011) 60-70.
  8. Akkaya, K., Younis, M., “A survey on routing protocols for wireless sensor networks”, Journal ofAd-Hoc networks, Vol. 3 (2005), 325–349.
  9. Asorey-Cachedaa, R., Garcia-Sanchezb, A.J., Garcia-Sanchezb, F., Garcia-Harob, J., “A survey on non-linear optimization problems in wireless sensor networks”, Journal of Network and Computer Applications, Vol. 82 (2017), 1–20.
  10. Hruschka, E.R., Ricardo, J.G.B., Freitas, A.A., “A Survey of Evolutionary Algorithms for Clustering”, Journal of IEEE Transactions on Systems, Vol. 39 (2009), 133-155.
  11. Shah, R.C., Rabaey, J.M., “Energy aware routing for low energy ad hoc sensor networks”, Wireless Communications and Networking Conference, WCNC (2002), Vol. 1, 350-355.
  12. Arjunan, S., Pothula, S., “A survey on unequal clustering protocols in Wireless Sensor Networks”, Journal of Computer and Information Sciences, Vol. 31 (2017).
  13. Karaboga, D., Okdem, S., Ozturk, C., “Cluster based wireless sensor network routing using artificial bee colony algorithm,” Journal of Wireless Networks, Vol. 18 (2012), 847-860.
  14. Vaidyanathan, S., Vaidyanathan, M., “Wireless Sensor Networks-Issues & Challenges”, Journal of Information Systems: Behavioral & Social Methods, 2011, 7-12.
  15. Boyinbode, O., Le, H., Mbogho A., “A Survey on Clustering Algorithms for Wireless Sensor Networks”, 13th International Conference on Network-Based Information Systems (NBiS) 2010, Japan.
  16. Ye, M., Li, C., Chen G., Wu, J., “An Energy Efficient Clustering Scheme in Wireless Sensor Networks”, Ad-Hoc & Sensor Wireless Networks, , Vol.1 (2006), 1-21.
  17. Kaur, S., Naaz Mir, R., “Clustering in Wireless Sensor Networks- A Survey”, International Journal of Computer Network and Information Security, Vol. 6 (2016), 38-51.
  18. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H., “Energy-efficient communication protocol for wireless microsensor networks”, the 33rd IEEE Annual Hawaii International Conference on in System Sciences, Vol. 2 (2000), 10 -16.
  19. Rahmanian, A., Omranpour, H., Akbari, M., “A novel Genetic Algorithm in LEACH-C routing protocol for sensor networks”, 24th Canadian Conference on Electrical and Computer Engineering (CCECE) 2011, Canada.
  20. Younis, O., Fahmy, S., “HEED: A Hybrid Energy-Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks”, Journal of IEEE Transactions on Mobile Computing, Vol. 3 (2004), No. 4, 366-379.
  21. Hosseinirad, S.M., Basu, S.K., “Wireless sensor network design through Genetic Algorithm”, Journal of AI and Data Mining, Vol. 2 (2014), No. 1, 85-96.
  22. Hosseinirad, S.M., Alimohammadi, M., Basu, S.K., Pouyan, A.A., “LEACH Routing Algorithm Optimization through Imperialist Approach” International Journal of EngineeringTransaction A: Basics, Vol. 27 (2013), No. 1, 39-50.
  23. Haupt, R.L., Haupt, S.E., “Practical Genetic Algorithms”, John Wiley & Sons, 2004.
  24. Karaboga, D., Okdem, S., Ozturk, C.,“Cluster based wireless sensor network routing using artificial bee colony algorithm”, Journal of Wireless Networks, Vol. 18 (2012), No. 7, 847-860.
  25. Blum, C., Li, X., “Swarm intelligence in optimization”, Springer, 2008.
  26. Hussain, S., Matin, A.W., Islam, O., “Genetic Algorithm for hierarchical wireless sensor networks,” Journal of Networks, Vol. 2 (2007), No. 5, 87-97.