Skip to main content

Energy Aware Optimized Hierarchical Routing Technique for Wireless Sensor Networks

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 723))

Abstract

Wireless Sensor Networks (WSNs) ordinarily be composed of a large number of low-power sensor nodes which having several functions, that are a battery powered, and thus have very limited energy capacity. To lengthen the operational lifetime of a sensor network, energy efficiency should be considered in every aspect of sensor network design. In this paper, Enhanced Hierarchical Routing Technique (EHRT) is proposed to overcome the constraint of limited energy capacity of sensor nodes which enhancing the network lifetime and the energy efficiency. The suggested technique is a cluster-based routing which optimizes the low-energy adaptive clustering hierarchy routing technique (LEACH) by using a modified artificial fish swarm algorithm (AFSA). This modified AFSA selects the optimum clusters’ head (CHs) locations by applying a number of behaviors following, preying and swarming on each cluster separately and using a modified fitness function to compare these behaviors’ outputs to select the best CHs locations for each cluster separately. A framework for evaluating the performance is constructed and applied to verify the efficiency of the suggested technique comparing to other energy efficient routing techniques; optimized hierarchical routing technique (OHRT), low-energy adaptive clustering hierarchy (LEACH), and particle swarm optimized (PSO) routing techniques. The proposed technique yields best results than other techniques OHRT, LEACH, and PSO in terms of energy consumption and network lifetime. It reduces the energy dissipation by factor 0.7 compared with OHRT.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38, 393–422 (2002)

    Article  Google Scholar 

  2. Zheng, J., Jamalipour, A.: Wireless Sensor Networks: A Networking Perspective. Wiley, Hoboken (2009)

    Book  MATH  Google Scholar 

  3. Iqbal, M., Naeem, M., Anpalagan, A., Ahmed, A., Azam, M.: Wireless sensor network optimization: multi-objective paradigm. Sensors 15, 17572–17620 (2015)

    Article  Google Scholar 

  4. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: 2000 Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, vol. 2, 10 p. (2000)

    Google Scholar 

  5. Manjeshwar, A., Agrawal, D.P.: TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In: null, p. 30189a (2001)

    Google Scholar 

  6. Sendra, S., Parra, L., Lloret, J., Khan, S.: Systems and algorithms for wireless sensor networks based on animal and natural behavior. Int. J. Distrib. Sens. Netw. 11, 625972 (2015)

    Article  Google Scholar 

  7. Guo, T., Zhao, H.: An Improvement of AFSA in global search with scout swarms. In: 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013) (2013)

    Google Scholar 

  8. Dhiman, V.: BIO inspired hybrid routing protocol for wireless sensor networks. Int. J. Adv. Res. Eng. Technol. 1, 33–36 (2013)

    Google Scholar 

  9. Bhaduri, S.N., Fogarty, D.: New methods in ant colony optimization using multiple foraging approach to increase stability. Advanced Business Analytics, pp. 131–138. Springer, Singapore (2016).

    Google Scholar 

  10. El-Said, S.A., Osamaa, A., Hassanien, A.E.: Optimized hierarchical routing technique for wireless sensors networks. Soft Comput. 20, 4549–4564 (2016)

    Article  Google Scholar 

  11. Xing, B., Gao, W.-J.: Fish inspired algorithms. Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. ISRL, vol. 62, pp. 139–155. Springer, Cham (2014).

    Chapter  Google Scholar 

  12. Ganesan, T., Vasant, P., Elamvazuthi, I.: Advances in Metaheuristics: Applications in Engineering Systems. CRC Press, Boca Raton (2016)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nermeen M. Hamza .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hamza, N.M., El-said, S.A., Attia, E.R.M., Abdalla, M.I. (2018). Energy Aware Optimized Hierarchical Routing Technique for Wireless Sensor Networks. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_60

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-74690-6_60

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74689-0

  • Online ISBN: 978-3-319-74690-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics