Abstract
Since sensor nodes make use of battery energy, energy consumption and limitation of sensor nodes is regarded as a fundamental challenge and problem in wireless sensor nodes. Recently, in wireless sensor networks (WSNs), clustering-based energy-aware routing protocols divide neighboring nodes into separate clusters and select local cluster heads so as to combine and transmit information of each of the clusters to the central station. In this way, they attempt to maintain energy consumption balance by the network nodes. When compared with other methods, clustering methods have been able to achieve the best efficiency with regard to the enhancement of network lifetime. In this paper, using cuckoo optimization algorithm, an energy-aware clustering-based routing protocol was proposed in WSNs which is able to cluster the network and select optimal cluster heads. The proposed method considered four criteria with regard to selecting cluster heads in the targeted cuckoo algorithm, namely the remaining energy of nodes, distance to the base station, within-cluster distances and between cluster distances. The results of simulating the proposed method in Matlab environment indicated it is better than other algorithms such as low energy adaptive clustering hierarchical (LEACH), application-specific low power routing, LACH-EP and LEACH with distance-based threshold with regard to the first node die on average and packet delivery rate for six scenario.
Similar content being viewed by others
References
Arya, R., & Sharma, S. (2015). Analysis and optimization of energy of sensor node using ACO in wireless sensor network. Procedia Computer Science, 45, 681–686.
KeyKhosravi, D., Ghaffari, A., Hosseinalipour, A., & Khasragi, B. A. (2010). New clustering protocol to decrease probability failure nodes and increasing the lifetime in WSNs. International Journal of Advanced Computer Technology, 2, 117–121.
Ghaffari, A., & Rahmani, A. (2008). Fault tolerant model for data dissemination in wireless sensor networks. In Information technology, 2008. ITSim 2008. International symposium on (pp. 1–8).
Ghaffari, A. (2014). Designing a wireless sensor network for ocean status notification system. Indian Journal of Science and Technology, 7, 809–814.
Singh, R., & Verma, A. K. (2017). Energy efficient cross layer based adaptive threshold routing protocol for WSN. AEU-International Journal of Electronics and Communications, 72, 166–173.
Azari, L., & Ghaffari, A. (2015). Proposing a novel method based on network-coding for optimizing error recovery in wireless sensor networks. Indian Journal of Science and Technology, 8, 859–867.
Ghaffari, A., & Nobahary, S. (2015). FDMG: Fault detection method by using genetic algorithm in clustered wireless sensor networks. Journal of AI and Data Mining, 3(1), 47–57.
Ghaffari, A. (2017). Real-time routing algorithm for mobile ad hoc networks using reinforcement learning and heuristic algorithms. Wireless Networks, 23(3), 703–714.
Alizadeh, S., & Ghaffari, A. (2010). An energy-efficient hierarchical clustering protocol in wireless sensor networks. In Computer science and information technology (ICCSIT), 2010 3rd IEEE international conference on (pp. 413–418).
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In HICSS’00. Proceedings of the 33rd Hawaii international conference on System sciences (pp. 3005–3014).
Mottaghinia, Z., & Ghaffari, A. (2016). A unicast tree-based data gathering protocol for delay tolerant mobile sensor networks. Information Systems & Telecommunication, 59, 1–12.
Mohammadi, R., & Ghaffari, A. (2015). Optimizing reliability through network coding in wireless multimedia sensor networks. Indian Journal of Science and Technology, 8, 834–841.
Abuarqoub, A., Hammoudeh, M., Adebisi, B., Jabbar, S., Bounceur, A., & Al-Bashar, H. (2017). Dynamic clustering and management of mobile wireless sensor networks. Computer Networks, 117, 62–75.
Shokouhifar, M., & Jalali, A. (2017). Optimized sugeno fuzzy clustering algorithm for wireless sensor networks. Engineering Applications of Artificial Intelligence, 60, 16–25.
Mann, P. S., & Singh, S. (2017). Energy efficient clustering protocol based on improved metaheuristic in wireless sensor networks. Journal of Network and Computer Applications, 83, 40–52.
Moon, S.-H., Park, S., & Han, S.-J. (2017). Energy efficient data collection in sink-centric wireless sensor networks: A cluster-ring approach. Computer Communications, 101, 12–25.
Sengottuvelan, P., & Prasath, N. (2017). BAFSA: Breeding artificial fish swarm algorithm for optimal cluster head selection in wireless sensor networks. Wireless Personal Communications: An International Journal, 94, 1979–1991.
Amgoth, T., & Jana, P. K. (2015). Energy-aware routing algorithm for wireless sensor networks. Computers & Electrical Engineering, 41, 357–367.
Hammoudeh, M., & Newman, R. (2015). Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance. Information Fusion, 22, 3–15.
Elhabyan, R. S., & Yagoub, M. C. (2015). Two-tier particle swarm optimization protocol for clustering and routing in wireless sensor network. Journal of Network and Computer Applications, 52, 116–128.
Mammu, A. S. K., Sharma, A., Hernandez-Jayo, U., & Sainz, N. (2013). A novel cluster-based energy efficient routing in wireless sensor networks. In Advanced information networking and applications (AINA), 2013 IEEE 27th international conference on, (pp. 41–47).
Lakhlef, H. (2015). A multi-level clustering scheme based on cliques and clusters for wireless sensor networks. Computers & Electrical Engineering, 48, 436–450.
Sun, D., Huang, X., Liu, Y., & Zhong, H. (2013). Predictable energy aware routing based on dynamic game theory in wireless sensor networks. Computers & Electrical Engineering, 39, 1601–1608.
Ke, C.-K., Chen, Y.-L., Chang, Y.-C., & Zeng, Y.-L. (2016). Opportunistic large array concentric routing algorithms with relay nodes for wireless sensor networks. Computers & Electrical Engineering, 56, 350–365.
Zeng, B., & Dong, Y. (2016). An improved harmony search based energy-efficient routing algorithm for wireless sensor networks. Applied Soft Computing, 41, 135–147.
Barekatain, B., Dehghani, S., & Pourzaferani, M. (2015). An energy-aware routing protocol for wireless sensor networks based on new combination of genetic algorithm & k-means. Procedia Computer Science, 72, 552–560.
Kong, L., Xiang, Q., Liu, X., Liu, X.-Y., Gao, X., Chen, G., et al. (2016). ICP: Instantaneous clustering protocol for wireless sensor networks. Computer Networks, 101, 144–157.
Thakkar, A., & Kotecha, K. (2015). A new Bollinger Band based energy efficient routing for clustered wireless sensor network. Applied Soft Computing, 32, 144–153.
Azharuddin, M., Kuila, P., & Jana, P. K. (2015). Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks. Computers & Electrical Engineering, 41, 177–190.
Kang, S. H., & Nguyen, T. (2012). Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters, 16, 1396–1399.
Baradaran, A. A. & Navi, K. (2017). CAST-WSN: The presentation of new clustering algorithm based on Steiner tree and C-means algorithm improvement in wireless sensor networks. Wireless Personal Communications. doi:10.1007/s11277-017-4572-x.
Akila, I., & Venkatesan, R. (2016). A cognitive multi-hop clustering approach for wireless sensor networks. Wireless Personal Communications: An International Journal, 90, 729–747.
Sivaraj, C., Alphonse, P., & Janakiraman, T. (2017). Independent neighbour set based clustering algorithm for routing in wireless sensor networks. Wireless Personal Communications, 1–23.
Rajendra Prasad, D., Naganjaneyulu, P., & Satya Prasad, K. (2017). A hybrid swarm optimization for energy efficient clustering in multi-hop wireless sensor network. Wireless Personal Communications: An International Journal, 94, 2459–2471.
Haseeb, K., Bakar, K. A., Ahmed, A., Darwish, T., & Ahmed, I. WECRR: Weighted energy-efficient clustering with robust routing for wireless sensor networks. Wireless Personal Communications, 1–27.
Oladimeji, M. O., Turkey, M., & Dudley, S. (2017). HACH: Heuristic Algorithm for Clustering Hierarchy protocol in wireless sensor networks. Applied Soft Computing, 55, 452–461.
Jia, J.-g., He, Z.-w., Kuang, J.-m., & Mu, Y.-h. (2010). An energy consumption balanced clustering algorithm for wireless sensor network. In 2010 6th international conference on wireless communications networking and mobile computing (WiCOM) (pp. 1–4).
Shokouhifar, M., & Jalali, A. (2015). A new evolutionary based application specific routing protocol for clustered wireless sensor networks. AEU-International Journal of Electronics and Communications, 69, 432–441.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Khabiri, M., Ghaffari, A. Energy-Aware Clustering-Based Routing in Wireless Sensor Networks Using Cuckoo Optimization Algorithm. Wireless Pers Commun 98, 2473–2495 (2018). https://doi.org/10.1007/s11277-017-4983-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-017-4983-8