Abstract
The limited battery power supply system makes energy efficiency a major concern in WSNs. An effective method is to organize the sensors into clusters to avoid redundancy and long-distance data transmission in the network. In traditional clustering methods, the cluster heads not only serve as leaders to collect the coming data from their cluster members but also play the roles of relay nodes to transmit the aggregated data to the sink node simultaneously, such that CHs consume much more energy than ordinary nodes. From the perspective of energy balancing, it is better to select the different nodes as CHs and relay nodes. In this paper, an energy-efficient overlapping clustering protocol is proposed, which assigns the boundary nodes in the overlapping area to relay the aggregated data to the sink node. Thereby the relay nodes are uniformly distributed near the CHs. Comparisons with LEACH and SEECH protocols show that the proposed protocol achieves better performance in terms of lifetime and load-balancing.
Similar content being viewed by others
References
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38, 393–422.
Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52, 2292–2330.
Abdelaal, M., & Theel, O. (2014). Recent energy-preservation endeavours for longlife wireless sensor networks: A concise survey. In IEEE 7th conference onwireless and optical communications networks (WOCN) (pp. 1–7).
Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104–122.
Keskin, M. E., Altanel, I. K., Aras, N., & Ersoy, C. (2014). Wireless sensor network lifetime maximization by optimal sensor deployment, activity scheduling, data routing and sink mobility. Ad Hoc Networks, 17(6), 18–36.
Ishmanov, F., Malik, A. S., & Kim, S. W. (2011). Energy consumption balancing (ECB) issues and mechanisms in wireless sensor networks (WSNs): A comprehensive overview. European Transactions on Telecommunications, 22(4), 151–167.
Afsar, M. M., & Tayarani-N, M. H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226.
Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30, 2826–2841.
Liu, A. F., Zhang, P. H., & Chen, Z. G. (2011). Theoretical analysis of the lifetime and energy hole in cluster based wireless sensor networks. Journal of Parallel and Distributed Computing, 71(10), 1327–1355.
Mhatre, V., & Rosenberg, C. (2004). Design guidelines for wireless sensor networks: Communication, clustering and aggregation. Ad Hoc Networks, 2, 45–63.
Lai, W. K., Fan, C. S., & Lin, L. Y. (2012). Arranging cluster sizes and transmission ranges for wireless sensor networks. Information Sciences, 183, 117–131.
Chen, G. H., Li, C. F., Ye, M., & Wu, J. (2009). An unequal cluster-head routing protocols in wireless sensor networks. Wireless Networks, 15, 193–207.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.
Liu, Z. X., Zheng, Q. C., X, L., & Guan, X. P. (2012). A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Future Generation Computer Systems, 28(5), 780–790.
Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. In Second international workshop on sensor and actor network protocols and applications (SANPA 2004).
Qing, L., Zhu, Q., & Wang, M. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communications, 29(12), 2230–2237.
Zhou, H., Wu, Y., Hu, Y., & Xie, G. Z. (2010). A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks. Computer Communications, 33(15), 1843–1849.
Zhen, H., Li, Y., & Zhang, G. J. (2013). Efficient and dynamic clustering scheme for heterogeneous multi-level wireless sensor networks. Acta Automatica Sinica, 39(4), 454–460.
Xu, K. N., Hassanein, H., Takahara, G., & Wang, Q. H. (2010). Relay node deployment strategies in heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 9(2), 145–159.
Wang, F., Wang, D., & Liu, J. C. (2011). Traffic-aware relay node deployment: Maximizing lifetime for data collection wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22(8), 1415–1423.
Cui, Q., Yang, X. J., Tao, X. F., & Zhang, P. (2014). Optimal energy-efficient relay deployment for the bidirectional relay transmission schemes. IEEE Transactions on Vehicular Technology, 63(6), 2625–2641.
Chang, J. Y., & Lin, Y. S. (2014). A clustering deployment scheme for base stations and relay stations in multi-hop relay networks. Computers and Electrical Engineering, 40, 407–420.
Liao, Y., Qi, H., & Li, W. Q. (2013). Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks. IEEE Sensor Networks, 13(5), 1056–1498.
Kuila, P., Gupta, S. K., & Jana, P. K. (2013). A novel evolutionary approach for load balanced clustering problem for wireless sensor networks. Swarm and Evolutionary Computation, 12, 48–56.
Chanak, P., Banerjee, I., & Rahaman, H. (2015). Load management scheme for energy holes reduction in wireless sensor networks. Computers and Electrical Engineering, 48, 1–15.
Liu, T., Li, Q. R., & Liang, P. (2012). An energy-balancing clustering approach for gradient-based routing in wireless sensor networks. Computer Communications, 35, 2150–2161.
Baranidharan, B., & Santhi, B. (2016). DUCF: Distributed load balancing unequal clustering in wireless sensor networks using Fuzzy approach. Applied Soft Computing, 40, 495–506.
Tarhani, M., Kavian, Y., & Siavoshi, S. (2014). SEECH: Scalable energy efficient clustering hierarchy protocol in wireless sensor networks. IEEE Sensor Journal, 14(11), 3944–3954.
Liu X. F., et al. (2011). Energy efficient clustering for WSN-based structural health monitoring. In IEEE INFOCOM (pp. 2768–2776).
Ammar, I., Miskeen, G., & Awan, I. (2013). Overlapped schedules with centralized clustering for wireless sensor networks. In IEEE 27th international conference on advanced information networking and applications (pp. 33–40).
Kalyanasundaram, B., & Younis, M. (2013). Using mobile data collectors to federate clusters of disjoint sensor network segments. In IEEE ICC-Ad-hoc and sensor networking symposium (pp. 1496–1500).
Dai, G. Y., et al. (2015). A novel distributed clustering-based MDS algorithm for nodes localization in WSNs. International Journal of Grid Distribution Computing, 8(2), 79–90.
Youssef, M. A., Youssef, A., & Younis, F. (2009). Overlapping multihop clustering for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 20(12), 1844–1856.
Amini, A., Vahdatpour, A., Xu, W. Y., Gerla, M., & Sarrafzadeh, M. (2012). Cluster size optimization in sensor networks with decentralized cluster-based protocols. Computer Communications, 35, 207–220.
Acknowledgements
This work is supported by National Natural Science Foundation (NNSF) from China (61273073, 61374107).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hu, Y., Niu, Y. An energy-efficient overlapping clustering protocol in WSNs. Wireless Netw 24, 1775–1791 (2018). https://doi.org/10.1007/s11276-016-1434-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-016-1434-5