DOI QR코드

DOI QR Code

Energy-Efficient Routing Protocol for Wireless Sensor Networks Based on Improved Grey Wolf Optimizer

  • Zhao, Xiaoqiang (School of Communication and Information, Xi'an University of Posts and Telecommunications) ;
  • Zhu, Hui (School of Communication and Information, Xi'an University of Posts and Telecommunications) ;
  • Aleksic, Slavisa (Institute of Communications Engineering, Leipzig University of Telecommunications) ;
  • Gao, Qiang (School of Communication and Information, Xi'an University of Posts and Telecommunications)
  • Received : 2017.11.06
  • Accepted : 2018.01.10
  • Published : 2018.06.30

Abstract

To utilize the energy of sensor nodes efficiently and extend the network lifetime maximally is one of the primary goals in wireless sensor networks (WSNs). Thus, designing an energy-efficient protocol to optimize the determination of cluster heads (CHs) in WSNs has become increasingly important. In this paper, we propose a novel energy-efficient protocol based on an improved Grey Wolf Optimizer (GWO), which we refer to as Fitness value based Improved GWO (FIGWO). It considers a fitness value to improve the finding of the optimal solution in GWO, which ensures a better distribution of CHs and a more balanced cluster structure. According to the distance to the CHs and the BS, sensor nodes' transmission distance are recalculated to reduce the energy consumption. Simulation results demonstrate that the proposed approach can prolong the stability period of the network in comparison to other algorithms, namely by 31.5% in comparison to SEP, and even by 57.8% when compared with LEACH protocol. The results also show that the proposed protocol performs well over the above comparative protocols in terms of energy consumption and network throughput.

Keywords

References

  1. S. Ehsan and B. Hamdaoui, "A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless Multimedia Sensor Networks," IEEE Communications Surveys & Tutorials, vol 14, no.2, pp. 265-278, 2012. https://doi.org/10.1109/SURV.2011.020211.00058
  2. S. S. Wang and Z. P. Chen, "LCM: A Link-Aware Clustering Mechanism for Energy-Efficient Routing in Wireless Sensor Networks," IEEE Sensors Journal, vol 13, no.2, pp. 728-736, 2013. https://doi.org/10.1109/JSEN.2012.2225423
  3. N. Wang, Y. Zhou, and W. Xiang, "An Energy Efficient Clustering Protocol for Lifetime Maximization in Wireless Sensor Networks," in Proc. of IEEE Conf. on Global Communications(GLOBECO), pp. 1-6, Dec. 4-8, 2016.
  4. M. M. Afsar and M. H. Tayarani-N, "Clustering in sensor networks: A literature survey," Journal of Network & Computer Applications, vol 46, pp. 198-226, 2014. https://doi.org/10.1016/j.jnca.2014.09.005
  5. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-Efficient Communication Protocol for Wireless Microsensor Networks," in Proc. of IEEE international Conf. on System Sciences, pp.10, Jan. 7-7, 2000.
  6. P. G. Naranjo, M. Shojafar, H. Mostafaei, Z. Pooranian and E. Baccarelli, "P-sep: a prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks," Journal of Supercomputing, vol 73 no.2, 733-755, 2017. https://doi.org/10.1007/s11227-016-1785-9
  7. S. H. H. Nazhad, M. Shojafar, S. Shamshirband and M. Conti, "An efficient routing protocol for the qos support of large scale MANETs" International Journal of Communication Systems, vol 31, no.2, pp. 1-18, 2017.
  8. A. Ray and D. De, "Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network," IETWireless Sensor Systems, vol 6, no.6, pp. 181-191, 2016. https://doi.org/10.1049/iet-wss.2015.0087
  9. C. L. Ma, N. Liu and Y. Ruan, "A Dynamic and Energy-Efficient Clustering Algorithm in Large-Scale Mobile Sensor Networks," International Journal of Distributed Sensor Networks, vol 9, no. 11, pp. 1-8, 2013.
  10. G. Y. Park, H. Kim, H. W. Jeong and H. Y. Youn, "A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network," in Proc. of IEEE International Conf on Advanced Information networking and Applications Workshops(WAINA), pp.910-915, March. 25-28, 2013.
  11. A. Ahmadi, M. Shojafar, S. F. Hajeforosh, M. Dehghan and M. Singhal, "An efficient routing algorithm to preserve k-coverage in wireless sensor networks," Journal of Supercomputing, vol. 68, no. 2, pp. 599-623, 2014. https://doi.org/10.1007/s11227-013-1054-0
  12. N. A. Al-Aboody and H. S. Al-Raweshidy, "Grey wolf optimization-based energy-efficient routing protocol for heterogeneous wireless sensor networks," in Proc. of IEEE International Symposium on Computational and Business Intelligence(ISCBI), pp. 101-107, Sept. 5-7, 2016.
  13. H. Mostafaei and M. Shojafar, "A New Meta-heuristic Algorithm for Maximizing Lifetime of Wireless Sensor Networks," Kluwer Academic Publishers, vol 82, no. 2, pp. 723-742, 2015. https://doi.org/10.1007/s11277-014-2249-2
  14. S. Mirjalili, S. M. Mirjalili, and A. Lewis, "Grey Wolf Optimizer," Advances in Engineering Software, vol 69, no.3, pp. 46-61, 2014. https://doi.org/10.1016/j.advengsoft.2013.12.007