Skip to main content

Cluster-Based Wireless Sensor Networks Using Ant Colony Optimization

  • Conference paper
  • First Online:
International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 (ICICI 2018)

Abstract

Nodes in the Wireless sensor network (WSN) have the limited power, memory and battery capacity. In this work, we propose an efficient routing algorithm called Cluster Based Wireless Sensor Network using Ant Colony Optimization (CBACO). The Cluster Heads (CH) are selected based on the cost derived from node parameters remaining energy, number of neighbours and distance to base station. The weighted average method is used to compute cost. The routing processes are established in two levels. The cluster member to cluster head data transmission is handled at level one and in the second level path finding process between cluster head to base station handled by Ant Colony Optimization (ACO) method which is the biologically inspired optimization technique. All the cluster head nodes are participate in the second level inter-cluster routing operation. The performance of the CBACO algorithm in terms of delay is minimized by using the clustering method and ACO method. The efficiency of the proposed algorithm is analysed by compare with existing routing algorithm which uses LEACH and ACO method. The results indicate that our proposed work achieves low energy consumption and high throughput.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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

Institutional subscriptions

Similar content being viewed by others

References

  1. Abbasi, A., Younis, M.: A survey on clustering algorithms for wireless sensor networks. Comput. Commun. 30(14–15), 2826–2841 (2007)

    Article  Google Scholar 

  2. Salehpour, A.-A., Mirmobin, B., Afzali-Kusha, A., Mohammadi, S.: An energy efficient routing protocol for cluster-based wireless sensor networks using ant colony optimization. IEEE-2008 (2008)

    Google Scholar 

  3. Nayyar, A., Singh, R.: Ant Colony Optimization (ACO) based routing protocols for wireless sensor networks (WSN): a survey. (IJACSA). Int. J. Adv. Comput. Sci. Appl. 8(2), 148–155 (2017)

    Google Scholar 

  4. Amiri, E., Keshavarz, H., Alizadeh, M., Zamani, M., Khodadadi, T.: Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization. Int. J. Distrib. Sens. Netw. 2014, 17. http://dx.doi.org/10.1155/2014/768936,Article ID 768936, Hindawi Publishing Corporation

  5. Akyildiz, F., Su, W., Sankarasubramaniam, Y., Cyirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38(4), 393–422 (2002)

    Article  Google Scholar 

  6. Chen, G., Guo, T. D., Yang, W.G., Zhao, T.: An improved ant based routing protocol in Wireless Sensor Networks. In: Proceedings of International Conference on Collaborative Computing: Networking, Applications and Worksharing, pp. 1–7, November 2006

    Google Scholar 

  7. DiCaro, G., Dorigo, M.: AntNet: distributed stigmergetic control for communications networks. J. Artif. Intell. Res. (JAIR) 9, 317–365 (1998)

    Article  Google Scholar 

  8. Kim, J.-Y., Sharma, T., Brijesh Kumar, G.S.T., Berry, K., Lee, W.-H.: Intercluster ant colony optimization algorithm for wireless sensor network in dense environment. Int. J. Distrib. Sens. Netw. 2014, 10. http://dx.doi.org/10.1155/2014/457402, Article ID 457402, Hindawi Publishing Corporation

  9. Sohraby, K., Minoli, D., Znati, T.: Wireless Sensor Networks: Technology, Protocols, and Applications. Wiley & Sons Inc., New York (2007)

    Book  Google Scholar 

  10. Juan, L., Chen, S., Chao, Z.: Ant system based anycast routing in wireless sensor networks. In: Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing (WiCom 2007), pp. 2420–2423, September 2007

    Google Scholar 

  11. Dorigo, M., Caro, G.D.: The Ant Colony Optimization Metaheuristic, 1st edn. McGraw-Hill, London (1999)

    Google Scholar 

  12. Dorigo, M., Gambardella, L.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1, 53–66 (1997)

    Article  Google Scholar 

  13. Okdem, S., Karaboga, D.: Routing in wireless sensor net-works using an ant colony optimization (ACO) router chip. Sensors 9(2), 909–921 (2009)

    Article  Google Scholar 

  14. Okdem, S., Karaboga, D.: Routing in wireless sensor networks using an Ant Colony Optimization (ACO) Router Chip. Sensors 9, 909–921 (2009). https://doi.org/10.3390/s90200909

    Article  Google Scholar 

  15. Gupta, V., Sharma, S.K.: Cluster head selection using modified ACO. In: Das, K.N., Deep, K., Pant, M., Bansal, J.C., Nagar, A. (eds.) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. AISC, vol. 335, pp. 11–20. Springer, New Delhi (2015). https://doi.org/10.1007/978-81-322-2217-0_2

    Chapter  Google Scholar 

  16. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy- efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (HICSS), pp. 3005–3014, January 2000

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Rajasekaran .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rajasekaran, A., Nagarajan, V. (2019). Cluster-Based Wireless Sensor Networks Using Ant Colony Optimization. In: Hemanth, J., Fernando, X., Lafata, P., Baig, Z. (eds) International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. ICICI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-030-03146-6_5

Download citation

Publish with us

Policies and ethics