Skip to main content

Advertisement

Log in

Mutual Constraint Based GA Suggested Routing Algorithm for Improving QoS in Clustered MANETS

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Mobile Ad-Hoc Network is a compilation of self-organized wireless devices that momentarily interconnects to support communication. In conjunction with the network characteristics like mobile nature and infrastructure less, some external factors also influence network Quality of Service (QoS). To ensure QoS in the network, QoS based optimizations and routing algorithms have been anticipated that concentrate limited metrics or result in sub-optimal solutions. To bridge the gap between QoS sustainability and to resolve sub optimal solution, Genetic Algorithm (GA) based Quality of Service Routing (QR) is proposed. This routing incorporates clustering algorithm based on preference that is designed to co-exist with GA based QR under undisputed constraints. This generates prolonged communication with higher convergence, preventing earlier optimal solution drain caused due to unstable clusters and frequent neighbor replacements. The proposed GA–QR is evaluated using the network metrics: throughput, end-to-end delay, overhead, etc.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Seas, S., Yang, Z., & He, J. (2004). A survey on mobile ad hoc wireless network. Information Technology Journal, 3, 168–175.

    Article  Google Scholar 

  2. Meisel, M., Pappas, V., & Zhang, L. (2010). A taxonomy of biologically inspired research in computer networking. Computer Networks, 54(6), 901–916.

    Article  MATH  Google Scholar 

  3. Al-Ghazal, M., El-Sayed, A. & Kelash, H. (2007). Routing optimization using genetic algorithm in ad hoc networks. In 2007 IEEE International Symposium on Signal Processing and Information Technology.

  4. Abolhasan, M., Wysocki, T., & Dutkiewicz, E. (2004). A review of routing protocols for mobile ad hoc networks. Ad Hoc Networks, 2(1), 1–22.

    Article  Google Scholar 

  5. Narayanaswamy, S., Kawadia, V., Sreenivas, R. S. & Kumar, P. R. (2002). Ad-hoc networks. Theory architecture algorithm and implementation of the compow protocols. In Proc. of European wireless. Next generation wireless networks: Technologies, Protocols, Service and Applications, pp. 156–162.

  6. Olascuaga-Cabrera, J. G., Lopez-Mellado, E., Mendez-Vazquez, A., & Ramos-Corchado, F. F. (2011). A self-organization algorithm for robust networking of wireless devices. IEEE Sensors Journal, 11(3), 771–780.

    Article  Google Scholar 

  7. Yen, Y.-S., Chao, H.-C., Chang, R.-S., & Vasilakos, A. (2011). Flooding limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11–12), 2238–2250.

    Article  Google Scholar 

  8. Roy, B., Banik, S., Dey, P., Sanyal, S., & Chaki, N. (2012). Ant Colony based routing for mobile ad-hoc networks towards improved quality of services. Journal of Emerging Trends in Computing and Information Sciences, 3(1), 1–4.

    Google Scholar 

  9. Zheng, Z., Wang, H. & Yao, L. (2012). An artificial bee colony optimization algorithm for multicast routing. In Advanced Communication Technology (ICACT), 14th International Conference, IEEE, pp. 168–172.

  10. Liu, K., Chen, Z., Abraham, A., Cao, W., & Jing, S. (2012) Degree-constrained minimum spanning tree problem using genetic algorithm. In Nature and Biologically Inspired Computing (NaBIC), Fourth World Congress, IEEE, pp. 8–14.

  11. Beena, Sathya. (2012). A multi-objective optimization strategy based on GSO for the multicast routing problem. International Journal of Advanced Research in Computer Science and Software Engineering, 2(10), 326–333.

    Google Scholar 

  12. Wang, X., Cheng, H., & Huang, H. (2013). Constructing a MANET based on clusters. Wireless Personal Communications, 75(2), 1489–1510.

    Article  Google Scholar 

  13. Manfredi, S. (2013). Design of a multi-hop dynamic consensus algorithm over wireless sensor networks. Control Engineering Practice, 21(4), 381–394.

    Article  Google Scholar 

  14. Zahidi, S. Z. H., Aloul, F., Sagahyroon, A., & El-Hajj, W. (2013). Optimizing complex cluster formation in MANETs using SAT/ILP techniques. IEEE Sensors Journal, 13(6), 2400–2412.

    Article  Google Scholar 

  15. Nancharaiah, B., & Mohan, B. C. (2014). The performance of a hybrid routing intelligent algorithm in a mobile ad hoc network. Computers & Electrical Engineering, 40(4), 1255–1264.

    Article  Google Scholar 

  16. Ying, Z., & Changgang, J. (2014). A kind of routing algorithm for heterogeneous wireless sensor networks based on affinity propagation. In The 26th Chinese Control and Decision Conference (2014 CCDC).

  17. Ahmadi, M., Shojafar, M., Khademzadeh, A., Badie, K., & Tavoli, R. (2015). A hybrid algorithm for preserving energy and delay routing in mobile ad- hoc networks. Wireless Personal Communications, 85(4), 2485–2505. https://doi.org/10.1007/s11277-015-2916-y.

    Article  Google Scholar 

  18. Rajan, C., & Shanthi, N. (2015). Genetic based optimization for multicast routing algorithm for MANET. Sadhana, 40(8), 2341–2352.

    Article  MathSciNet  Google Scholar 

  19. Asraf, N. M., Ainon, R. N., & Keong, P. K. (2010). QoS parameter optimization using multi-objective genetic algorithm in MANETs. In 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.

  20. Striegel, A., & Manimaran, G. (2002). A survey of QoS multicasting issues. IEEE Communications Magazine, 40(6), 82–87.

    Article  Google Scholar 

  21. Delavar, A. G., Hoseyny, S., & Maghsoudi, R. (2012). BCO-based optimized heuristic strategies for QoS routing. The Journal of Mathematics and Computer Science, 5(2), 105–114.

    Google Scholar 

  22. Gavhale, M., & Saraf, P. D. (2016). Survey on algorithms for efficient cluster formation and cluster head selection in MANET. Procedia Computer Science, 78, 477–482.

    Article  Google Scholar 

  23. Thenmozhi, D. S., & Rajaram, M. (2011). An efficient passive approach for quality of service routing in MANETs. International Journal of Engineering Trends and Technology, 2(2), 61–66.

    Google Scholar 

  24. Krishna, P. V., Saritha, V., Vedha, G., Bhiwal, A., & Chawla, A. (2012). Quality-of-service-enabled ant colony-based multipath routing for mobile ad hoc networks. IET Communications, 6(1), 76.

    Article  MathSciNet  MATH  Google Scholar 

  25. Nivetha, S. K., & Asokan, R. (2014). Hybrid ACO-PSO based multi objective optimization for quality of service routing in mobile ad hoc networks. International Journal of Applied Engineering Research, 9(24), 24651–24668.

    Google Scholar 

  26. Kulkarni, S. B., & Yuvaraju, B. N. (2015). ENB cluster head selection algorithm for MANET. International Journal on Engineering Technology and Sciences, 2(1) 4–6.

    Google Scholar 

  27. Lee, C., & Jeong, T. (2011). FRCA: A fuzzy relevance-based cluster head selection algorithm for wireless mobile ad-hoc sensor networks. Sensors, 11(12), 5383–5401.

    Article  Google Scholar 

  28. Li, Y., & Yang, S. (2015). Research on cluster head selection algorithm based on QoS constraints in mobile ad hoc networks. In 2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA).

  29. Cheng, H., Yang, S., & Cao, J. (2013). Dynamic genetic algorithms for the dynamic load balanced clustering problem in mobile ad hoc networks. Expert Systems with Applications, 40(4), 1381–1392.

    Article  Google Scholar 

  30. Hua, Y., & Zhimei, L. (2016). A genetic-algorithm-based clustering protocol in MANET. In Proceedings of the 7th International Conference on Computing Communication and Networking TechnologiesICCCNT 16.

Download references

Acknowledgements

One of the authors (K. B. Gurumoorthy) gratefully acknowledges to Dr. A. Nirmal Kumar, from the Kumaraguru College of Technology, India for their scientific advices and for providing the necessary laboratory facilities to carry out this investigation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Nirmal Kumar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gurumoorthy, K.B., Nirmal Kumar, A. Mutual Constraint Based GA Suggested Routing Algorithm for Improving QoS in Clustered MANETS. Wireless Pers Commun 98, 2975–2991 (2018). https://doi.org/10.1007/s11277-017-5011-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-5011-8

Keywords

Navigation