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A Novel Routing Technique for Congestion Avoidance in WSN using Bat Algorithm

by Aditya Prakash, Noorinder Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 32
Year of Publication: 2018
Authors: Aditya Prakash, Noorinder Kaur
10.5120/ijca2018916847

Aditya Prakash, Noorinder Kaur . A Novel Routing Technique for Congestion Avoidance in WSN using Bat Algorithm. International Journal of Computer Applications. 180, 32 ( Apr 2018), 23-28. DOI=10.5120/ijca2018916847

@article{ 10.5120/ijca2018916847,
author = { Aditya Prakash, Noorinder Kaur },
title = { A Novel Routing Technique for Congestion Avoidance in WSN using Bat Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 180 },
number = { 32 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 23-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number32/29251-2018916847/ },
doi = { 10.5120/ijca2018916847 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:02:27.764725+05:30
%A Aditya Prakash
%A Noorinder Kaur
%T A Novel Routing Technique for Congestion Avoidance in WSN using Bat Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 32
%P 23-28
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nature inspired optimization algorithms are useful for solving different kind of engineering problems, combinatorial problems and many more. Bat Algorithm is one of the nature inspired techniques which fulfill the criteria of finding the optimized and better result, in solving most of the problems. Routing is one of the combinatorial optimization problems, which can be solved using Bat Algorithm. Many researchers have contributed in this field by proposing and developing one or the other techniques to solve the problem of routing. In this paper, Bat Algorithm is used to solve the same and the problem of congestion over optimal path is avoided by the proposed algorithm in wireless sensor network. Experimental results show that the hybridization of bat algorithm and congestion avoidance strategy proved to be efficient than queue based congestion avoidance strategy while solving problem at hand on the basis of mean, minimum, maximum and median values.

References
  1. Bhatt, M., Sharma, S., Luhach, A. K., & Prakash, A. (2016, September). Nature inspired route optimization in vehicular adhoc network. In Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), 2016 5th International Conference on (pp. 447-451). IEEE.
  2. Bhatt, M., Sharma, S., Prakash, A., Pandey, U. S., & Jyoti, K. (2016). Traffic Collision Avoidance in VANET Using Computational Intelligence. International Journal of Engineering and Technology.
  3. Jadhav, P., & Satao, R. (2016). A survey on opportunistic routing protocols for wireless sensor networks. Procedia Computer Science, 79, 603-609.
  4. Jung, S. G., Kang, B., Yeoum, S., & Choo, H. (2016). Trail-using ant behavior based energy-efficient routing protocol in wireless sensor networks. International Journal of Distributed Sensor Networks.
  5. Sharma, S., Luhach, A. K., & Jyoti, K. (2016, March). Research & analysis of advancements in BAT algorithm. In Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on (pp. 2391-2396). IEEE.
  6. Sharma, S., Luhach, A. K., & Jyoti, K. (2016). A Novel Approach of Load Balancing in Cloud Computing using Computational Intelligence.
  7. Shahi, B., Dahal, S., Mishra, A., Kumar, S. V., & Kumar, C. P. (2016). A Review Over Genetic Algorithm and Application of Wireless Network Systems. Procedia Computer Science, 78, 431-438.
  8. E. U. K. Selim Yılmaz, "A new modification approach on bat algorithm for solving optimization problems," Applied Soft Computing, vol. 28, pp. 259-275, 2015
  9. Singh, S. P., & Sharma, S. C. (2015). A survey on cluster based routing protocols in wireless sensor networks. Procedia computer science, 45, 687-695.
  10. C.-S. S.-F. H.-Y. L.-S. P.-T. T. Yi-Ting Chen, "A Guidable Bat Algorithm Based on Doppler Effect to Improve Solving Efficiency for Optimization Problems," Computational Collective Intelligence. Technologies and Applications, vol. 8733, pp. 373-383, 2014.
  11. F. V. C. Jonathan Pérez, "A New Bat Algorithm with Fuzzy Logic for Dynamical Parameter Adaptation and Its Applicability to Fuzzy Control Design," Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics, vol. 574, pp. 65-79, 2014.
  12. H.Djelloul, "Binary bat algorithm for graph coloring problem," in Second World Conference on Complex Systems (WCCS), 2014
  13. M. T. Adis Alihodzic, "Improved Hybridized Bat Algorithm for Global Numerical Optimization," in International Conference on Computer Modelling and Simulation,IEEE, 2014.
  14. M. G. A. M. M. S. Homayun Afrabandpey, "A Novel Bat Algorithm Based on Chaos for Optimization Tasks," in Iranian Conference on Intelligent Systems (ICIS),IEEE, 2014.
  15. S. M. M. X.-S. Y. Seyedali Mirjalili, "Binary bat algorithm," Neural Computing and Applications, pp. 663681, 2014.
  16. Sharma, M. (2014, July). Wireless sensor networks: Routing protocols and security issues. In Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on (pp. 1-5). IEEE.
  17. Topal, A. O., Altun, O., & Terolli, E. (2014, October). Dynamic virtual bats algorithm (dvba) for minimization of supply chain cost with embedded risk. In Modelling Symposium (EMS), 2014 European (pp. 58-64). IEEE.
  18. Y. Z. Liangliang Li, "A novel complex-valued bat algorithm," Neural Computing and Applications, vol. 25, no. 6, pp. 1369-1381, 2014.
  19. Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications, 36(2), 623-645.
  20. Prathap, U., Shenoy, P. D., Venugopal, K. R., & Patnaik, L. M. (2012, December). Wireless sensor networks applications and routing protocols: survey and research challenges. In Cloud and Services Computing (ISCOS), 2012 International Symposium on (pp. 49-56). IEEE.
  21. Saleem, M., Di Caro, G. A., & Farooq, M. (2011). Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions. Information Sciences, 181(20), 4597-4624.
  22. Kordon, A. K. (2010). Swarm intelligence: The benefits of swarms. In Applying Computational Intelligence (pp. 145-174). Springer Berlin Heidelberg.
  23. Yang, X. S. (2010). A new metaheuristic bat-inspired algorithm. Nature inspired cooperative strategies for optimization (NICSO 2010), 65-74.
  24. Zengin, A., & Tuncel, S. (2010). A survey on swarm intelligence based routing protocols in wireless sensor networks. International Journal of Physical Sciences, 5(14), 2118-2126.
  25. Camilo, T., Carreto, C., Silva, J. S., & Boavida, F. (2006, September). An energy-efficient ant-based routing algorithm for wireless sensor networks. In International Workshop on Ant Colony Optimization and Swarm Intelligence (pp. 49-59). Springer Berlin Heidelberg.
  26. Manshahia, M. S., Dave, M., & Singh, S. B. (2016). Improved Bat Algorithm Based Energy Efficient Congestion Control Scheme for Wireless Sensor Networks. Wireless Sensor Network, 8(11), 229.
Index Terms

Computer Science
Information Sciences

Keywords

Bat Algorithm Collision Routing WSN

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