A TDMA Based Energy Efficient Unequal Clustering Protocol for Wireless Sensor Network Using PSO

  • Biroju PapacharyEmail author
  • Allam Mahesh Venkatanaga
  • G. Kalpana
Part of the Intelligent Systems Reference Library book series (ISRL, volume 172)


To increase the network lifetime and to save energy clustering method can be used as in most multi hop networks Cluster top being near to primary stations use more energy because of elevated inter cluster communicate traffic load resulting in Hop spot difficulty. By select an Extra CH named as Surrogate Cluster Head (SCH) in order to restore network connectivity which is interrupted because of failure of MCH, this method uses TDMA to allot time slots.


Equipment trojan Field programmable gate arrays Dynamic partial reconfiguration True random number generator 


  1. 1.
    Yick, J., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Comput. Netw. 52(12), 2292–2330 (2018)CrossRefGoogle Scholar
  2. 2.
    Yigitel, M.A., Incel, O.D., Ersoy, C.: QoS-aware MAC protocols for wireless sensor networks: a survey. Comput. Netw. 55(8), 1982–2004 (2011)CrossRefGoogle Scholar
  3. 3.
    Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)CrossRefGoogle Scholar
  4. 4.
    Liu, A.F., Wu, X.Y., Chen, Z.G., Gui, G.H.: Research on the energy hole problem based on unequal cluster-radius for wireless sensor networks. Comput. Commun. 33(3), 302–321 (2010)CrossRefGoogle Scholar
  5. 5.
    Gupta, G., Younis, M.: Fault-tolerant clustering of wireless sensor networks. In: Proceedings of IEEE Conference on Wireless Communications and Networking, vol. 3, pp. 1579-1584 (2003)Google Scholar
  6. 6.
    Kulkarni, R.V., Venayagamoorthy, G.K.: Particle swarm optimization in wireless-sensor networks: a brief survey. IEEE Trans. Syst. Man Cybern. 41(2), 262–267 (2011)CrossRefGoogle Scholar
  7. 7.
    Jiang, C.J., Shi, W.R., Tang, X.L.: Energy-balanced unequal clustering protocol for wireless sensor networks. J. China Univ. Posts Telecommun. 17(4), 94–99 (2010)CrossRefGoogle Scholar
  8. 8.
    Latiff, N.A., Tsimenidis, C., Sharif, S.B.: Energy-aware clustering for wireless sensor networks using particle swarm optimization. In: Proceedings of IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 1–5 (2007)Google Scholar
  9. 9.
    Salehian, S., Subraminiam, S.K.: Unequal clustering by improved particle swarm optimization in wireless sensor network. Procedia Comput. Sci. 62, 403–409 (2005)CrossRefGoogle Scholar
  10. 10.
    Rao, P.S., Jana, P.K., Banka, H.: A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks. Wirel. Netw. 23(7), 2005–2020 (2017)CrossRefGoogle Scholar
  11. 11.
    Kaur, T., Kumar, D.: Particle swarm optimization-based unequal and fault tolerant clustering protocol for wireless sensor networks. IEEE Sens. J. 18(11), 4614–4622 (2018)CrossRefGoogle Scholar
  12. 12.
    Ramesh, G.P.: Performance analysis of traffic with optical broker for load balancing and multicasting in software defined data center networkingGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Biroju Papachary
    • 1
    Email author
  • Allam Mahesh Venkatanaga
    • 1
  • G. Kalpana
    • 1
  1. 1.Department of ECECMR Engineering CollegeHyderabadIndia

Personalised recommendations