Discrete Fireworks Algorithm for Clustering in Wireless Sensor Networks
Grouping the sensor nodes into clusters is an approach to save energy in wireless sensor networks (WSNs). We proposed a new solution to improve the performance of clustering based on a novel swarm intelligence algorithm. Firstly, the objective function for clustering optimization is defined. Secondly, discrete fireworks algorithm for clustering (DFWA-C) in WSNs is designed to calculate the optimal number of clusters and to find the cluster-heads. At last, simulation is conducted using the DFWA-C and relevant algorithms respectively. Results show that the proposed algorithm could obtain the number of clusters which is close to the theoretical optimal value, and can effectively reduce energy consumption to prolong the lifetime of WSNs.
KeywordsClustering Discrete fireworks algorithm Optimization WSNs
This work is supported by National Natural Science Foundation of China under Grant No. 61502522.
- 1.Heinzelman, W.R., Chandrakasan, A.P., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: 33rd Hawaii International Conference on System Science, pp. 3005–3014 (2000)Google Scholar
- 5.Su, J.S., Guo, W.Z., Yu, C.L., Chen, G.L.: Fault-tolerance clustering algorithm with load-balance aware in Wireless sensor network. Chin. J. Comput. 37(2), 445–456 (2014)Google Scholar
- 6.Liao, F.B., Zhang, W.M.: Uneven clustering routing protocol for wireless sensor networks based on improved ant colony algorithm. Comput. Meas. Contr. 25(04), 147–152 (2017)Google Scholar
- 8.Tan, Y., Zheng, S.Q.: Recent advance in fireworks algorithm. CAAI Trans. Intell. Syst. 9(5), 516–528 (2014)Google Scholar
- 11.Xue, J.J., Wang, Y., Li, H., Xiao, J.: Discrete fireworks algorithm for aircraft mission planning. In: Tan, Y., Shi, Y., Niu, B. (eds.) ICSI 2016, LNCS. Lecture Notes in Computer Science, vol. 9712, pp. 544–551. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41000-5_54CrossRefGoogle Scholar