Wireless Personal Communications

, Volume 108, Issue 4, pp 2213–2228 | Cite as

An Improved Cluster Head Selection in Routing for Solar Energy-Harvesting Multi-heterogeneous Wireless Sensor Networks

  • Deepak SharmaEmail author
  • Amol P. Bhondekar


Wireless sensor network (WSN) is an effective and efficient technology for field information collection in Internet of Things arena. Generally, the lifetime of any WSN is restricted due to the limited battery capacities available with its sensor nodes. Replenishing the nodes’ batteries through energy-harvesting is becoming popular nowadays for improving the lifetime of the WSNs. Wireless communication activities of the sensor nodes take a major chunk of battery’s energy during WSN operations and to optimize the energy dissipation, energy-efficiency is given prime importance in routing decisions. The WSN heterogeneity (e.g., sensor nodes with heterogeneous sensing requirements, nodes with different energies, etc.) has become unavoidable and its effective exploitation further complicates the routing challenges. To fulfill the requirements of a realistic WSN system, this paper considers a multi-heterogeneity WSN scenario with sensors nodes having different initial energies and different traffic requirements along with solar energy-harvesting capabilities. An improved cluster-head selection based routing algorithm is proposed for the scenario, which exploits effectively the WSN heterogeneities in terms of energy, traffic and energy-harvesting. To highlight the performance of the proposed algorithm, the system is considered non energy-neutral, i.e. the energy dissipation of the system is higher than the system’s harvesting energy over a longer time period. The proposed algorithm, Energy-Harvesting, Traffic and Energy Aware Routing, improves the WSN stability period over existing routing algorithms under the scenario, where the stability period signifies the WSN lifetime till all the nodes are alive and represents the most reliable period of an operational WSN.


Wireless sensor networks Energy-harvesting Clustering Routing Heterogeneity Internet of Things 



  1. 1.
    Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.CrossRefGoogle Scholar
  2. 2.
    Akyildiz, I. F., & Vuran, M. C. (2010). Wireless sensor networks (Vol. 4). New York: Wiley.CrossRefGoogle Scholar
  3. 3.
    Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3(3), 325–349.CrossRefGoogle Scholar
  4. 4.
    Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications, 11(6), 6–28.CrossRefGoogle Scholar
  5. 5.
    Pantazis, N., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 15(2), 551–591.CrossRefGoogle Scholar
  6. 6.
    Tanwar, S., Kumar, N., & Rodrigues, J. J. (2015). A systematic review on heterogeneous routing protocols for wireless sensor network. Journal of Network and Computer Applications, 53, 39–56.CrossRefGoogle Scholar
  7. 7.
    Katiyar, V., Chand, N., & Soni, S. (2010). Clustering algorithms for heterogeneous wireless sensor network: A survey. International Journal of Applied Engineering Research, 1(2), 273.Google Scholar
  8. 8.
    Sharma, D., Ojha, A., & Bhondekar, A. P. (2018). Heterogeneity consideration in wireless sensor networks routing algorithms: A review. The Journal of Supercomputing. Scholar
  9. 9.
    Zhou, H., Wu, Y., Hu, Y., & Xie, G. (2010). A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks. Computer Communications, 33(15), 1843–1849.CrossRefGoogle Scholar
  10. 10.
    Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. Boston: Boston University Computer Science Department.Google Scholar
  11. 11.
    Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on, 2000 (Vol. 12, pp. 10). IEEE.Google Scholar
  12. 12.
    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
  13. 13.
    Kumar, D., Aseri, T. C., & Patel, R. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 662–667.CrossRefGoogle Scholar
  14. 14.
    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
  15. 15.
    Sharma, D., Bhondekar, A. P., Ojha, A., Shukla, A., & Ghanshyam, C. (2016). A traffic aware cluster head selection mechanism for hierarchical wireless sensor networks routing. In IEEE parallel, distributed and grid computing (PDGC), 2016 Fourth international conference on, 2016 (pp. 673–678). IEEE.Google Scholar
  16. 16.
    Sharma, D., Goap, A., Shukla, A., Priyanka, & Bhondekar, A. P. (2019). Traffic Heterogeneity Analysis in an Energy Heterogeneous WSN Routing Algorithm. In K. C., D. M., & K. R. (Eds.), Proceedings of 2nd international conference on communication, computing and networking. Lecture Notes in Networks and Systems (Vol. 46). Singapore: Springer.Google Scholar
  17. 17.
    Sharma, D., & Bhondekar, A. P. (2018). Traffic and energy aware routing for heterogeneous wireless sensor networks. IEEE Communications Letters, 22(8), 1608–1611.CrossRefGoogle Scholar
  18. 18.
    Wan, Z., Tan, Y., & Yuen, C. (2011). Review on energy harvesting and energy management for sustainable wireless sensor networks. In Communication technology (ICCT), 2011 IEEE 13th international conference on, 2011 (pp. 362–367). IEEE.Google Scholar
  19. 19.
    Basagni, S., Naderi, M. Y., Petrioli, C., & Spenza, D. (2013). Wireless sensor networks with energy harvesting. Mobile Ad Hoc Networking: The Cutting Edge Directions, 701–736.Google Scholar
  20. 20.
    Voigt, T., Dunkels, A., Alonso, J., Ritter, H., & Schiller, J. (2004). Solar-aware clustering in wireless sensor networks. In Computers and Communications, 2004. Proceedings. ISCC 2004. Ninth international symposium on, 2004 (Vol. 1, pp. 238–243). IEEE.Google Scholar
  21. 21.
    Xiao, M., Zhang, X., & Dong, Y. (2013). An effective routing protocol for energy harvesting wireless sensor networks. In Wireless communications and networking conference (WCNC), 2013 IEEE, 2013 (pp. 2080–2084). IEEE.Google Scholar
  22. 22.
    Bahbahani, M. S., & Alsusa, E. (2018). A cooperative clustering protocol with duty cycling for energy harvesting enabled wireless sensor networks. IEEE Transactions on Wireless Communications, 17(1), 101–111.CrossRefGoogle Scholar
  23. 23.
    Xu, X. N., Xiao, M. B., & Yan, W. (2015). Clustering routing algorithm for heterogeneous WSN with energy harvesting. In Applied Mechanics and materials, 2015 (Vol. 733, pp. 734–739). Trans Tech Publ.Google Scholar
  24. 24.
    Eu, Z. A., Tan, H.-P., & Seah, W. K. (2010). Opportunistic routing in wireless sensor networks powered by ambient energy harvesting. Computer Networks, 54(17), 2943–2966.CrossRefGoogle Scholar
  25. 25.
    Bozorgi, S. M., Rostami, A. S., Hosseinabadi, A. A. R., & Balas, V. E. (2017). A new clustering protocol for energy harvesting-wireless sensor networks. Computers & Electrical Engineering, 64, 233–247.CrossRefGoogle Scholar
  26. 26.
    Kansal, A., Hsu, J., Zahedi, S., & Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4), 32.CrossRefGoogle Scholar
  27. 27.
    Bergonzini, C., Brunelli, D., & Benini, L. (2009). Algorithms for harvested energy prediction in batteryless wireless sensor networks. In Advances in sensors and interfaces, 2009. IWASI 2009. 3rd international workshop on, 2009 (pp. 144–149). IEEE.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Academy of Scientific and Innovative Research (AcSIR)GhaziabadIndia
  2. 2.CSIR-Central Scientific Instruments Organisation (CSIR-CSIO)ChandigarhIndia

Personalised recommendations