Wireless Networks

, Volume 24, Issue 5, pp 1775–1791 | Cite as

An energy-efficient overlapping clustering protocol in WSNs

  • Yuan Hu
  • Yugang NiuEmail author


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.


Clustering Overlapping region Energy efficiency Load balancing 



This work is supported by National Natural Science Foundation (NNSF) from China (61273073, 61374107).


  1. 1.
    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38, 393–422.CrossRefGoogle Scholar
  2. 2.
    Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52, 2292–2330.CrossRefGoogle Scholar
  3. 3.
    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).Google Scholar
  4. 4.
    Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104–122.CrossRefGoogle Scholar
  5. 5.
    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.CrossRefGoogle Scholar
  6. 6.
    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.CrossRefGoogle Scholar
  7. 7.
    Afsar, M. M., & Tayarani-N, M. H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226.CrossRefGoogle Scholar
  8. 8.
    Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30, 2826–2841.CrossRefGoogle Scholar
  9. 9.
    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.CrossRefzbMATHGoogle Scholar
  10. 10.
    Mhatre, V., & Rosenberg, C. (2004). Design guidelines for wireless sensor networks: Communication, clustering and aggregation. Ad Hoc Networks, 2, 45–63.CrossRefGoogle Scholar
  11. 11.
    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.CrossRefGoogle Scholar
  12. 12.
    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.CrossRefGoogle Scholar
  13. 13.
    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.CrossRefGoogle Scholar
  14. 14.
    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.CrossRefGoogle Scholar
  15. 15.
    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).Google Scholar
  16. 16.
    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.CrossRefGoogle Scholar
  17. 17.
    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.CrossRefGoogle Scholar
  18. 18.
    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.CrossRefGoogle Scholar
  19. 19.
    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.CrossRefGoogle Scholar
  20. 20.
    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.CrossRefGoogle Scholar
  21. 21.
    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.CrossRefGoogle Scholar
  22. 22.
    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.CrossRefGoogle Scholar
  23. 23.
    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.Google Scholar
  24. 24.
    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.CrossRefGoogle Scholar
  25. 25.
    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.CrossRefGoogle Scholar
  26. 26.
    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.CrossRefGoogle Scholar
  27. 27.
    Baranidharan, B., & Santhi, B. (2016). DUCF: Distributed load balancing unequal clustering in wireless sensor networks using Fuzzy approach. Applied Soft Computing, 40, 495–506.CrossRefGoogle Scholar
  28. 28.
    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.CrossRefGoogle Scholar
  29. 29.
    Liu X. F., et al. (2011). Energy efficient clustering for WSN-based structural health monitoring. In IEEE INFOCOM (pp. 2768–2776).Google Scholar
  30. 30.
    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).Google Scholar
  31. 31.
    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).Google Scholar
  32. 32.
    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.CrossRefGoogle Scholar
  33. 33.
    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.CrossRefGoogle Scholar
  34. 34.
    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.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of EducationEast China University of Science and TechnologyShanghaiChina

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