Secured Energy Aware Projected 5G Network Architecture for Cumulative Performance in Advance Wireless Technologies

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Wireless Networks are known to be susceptible from different energy consumption issues and enormous algorithms are devised so far to improve the lifetime of sensor networks. Low-energy adaptive clustering hierarchy (LEACH) is one of the classical approaches that is adopted in many wireless implementations along with the variants of LEACH to escalate the overall life of nodes as well as network. Underwater Sensor Network or Acoustic Network (UWSN / UWAN) is a type of wireless network that is deployed under the ocean to monitor the movements of enemy or specific corporate purposes. The UWSN are having their base stations at the ships to keep and log the signals from underwater sensor nodes (USN). Such nodes are difficult to track physically and once their lifetime is over because of energy depletion, there is need to redeploy these nodes. To improve the lifetime of such underwater network, a novel and energy efficient approach of population based optimization is used in this research work with integration of soft computing. In this approach, the behavior of the bees in selecting their heads is adopted to form the dynamic cluster head in underwater wireless networks. It is found from the results that the bee colony based energy optimization approach is better as compared to the traditional approach in terms of multiple parameters.


  • Keywords

    Energy Optimization, Soft Computing, LEACH, Underwater Sensor Networks, UWSN

  • References

      [1] Wang, C.X., Haider, F., Gao, X., You, X.H., Yang, Y., Yuan, D., Aggoune, H., Haas, H., Fletcher, S. and Hepsaydir, E., 2014. Cellular architecture and key technologies for 5G wireless communication networks. IEEE Communications Magazine, 52(2), pp.122-130.

      [2] Rappaport, T.S., Sun, S., Mayzus, R., Zhao, H., Azar, Y., Wang, K., Wong, G.N., Schulz, J.K., Samimi, M. and Gutierrez, F., 2013. Millimeter wave mobile communications for 5G cellular: It will work!. IEEE access, 1, pp.335-349.

      [3] Ge, X., Cheng, H., Guizani, M. and Han, T., 2014. 5G wireless backhaul networks: challenges and research advances. IEEE Network, 28(6), pp.6-11.

      [4] Gupta, A. and Jha, R.K., 2015. A survey of 5G network: Architecture and emerging technologies. IEEE access, 3, pp.1206-1232.

      [5] Bangerter, B., Talwar, S., Arefi, R. and Stewart, K., 2014. Networks and devices for the 5G era. IEEE Communications Magazine, 52(2), pp.90-96.

      [6] Akyildiz, I.F., Wang, P. and Lin, S.C., 2016. SoftWater: Software-defined networking for next-generation underwater communication systems. Ad Hoc Networks, 46, pp.1-11.

      [7] Zhang, K., Mao, Y., Leng, S., Zhao, Q., Li, L., Peng, X., Pan, L., Maharjan, S. and Zhang, Y., 2016. Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks. IEEE Access, 4, pp.5896-5907.

      [8] Tehrani, M.N., Uysal, M. and Yanikomeroglu, H., 2014. Device-to-device communication in 5G cellular networks: challenges, solutions, and future directions. IEEE Communications Magazine, 52(5), pp.86-92.

      [9] Liu, Y., Zhang, Y., Yu, R. and Xie, S., 2015. Integrated energy and spectrum harvesting for 5G wireless communications. IEEE Network, 29(3), pp.75-81.

      [10] Dunbabin, M., Grinham, A. and Udy, J., 2009, December. An autonomous surface vehicle for water quality monitoring. In Australasian Conference on Robotics and Automation (ACRA) (pp. 2-4).

      [11] Pan, C.Z., Lai, X.Z., Yang, S.X. and Wu, M., 2013. An efficient neural network approach to tracking control of an autonomous surface vehicle with unknown dynamics. Expert Systems with Applications, 40(5), pp.1629-1635.

      [12] Shah, R.C. and Rabaey, J.M., 2002, March. Energy aware routing for low energy ad hoc sensor networks. In Wireless Communications and Networking Conference, 2002. WCNC2002. 2002 IEEE (Vol. 1, pp. 350-355). IEEE.

      [13] Jones, C.E., Sivalingam, K.M., Agrawal, P. and Chen, J.C., 2001. A survey of energy efficient network protocols for wireless networks. wireless networks, 7(4), pp.343-358.




Article ID: 21802
DOI: 10.14419/ijet.v7i4.17.21802

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.