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Reseach Article

Performance Evaluation of Re-Routing based Hybrid ACO-PSO based Routing Algorithm for MANETS

by Harkirat Kaur, Shivani Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 13
Year of Publication: 2016
Authors: Harkirat Kaur, Shivani Sharma
10.5120/ijca2016909973

Harkirat Kaur, Shivani Sharma . Performance Evaluation of Re-Routing based Hybrid ACO-PSO based Routing Algorithm for MANETS. International Journal of Computer Applications. 142, 13 ( May 2016), 12-15. DOI=10.5120/ijca2016909973

@article{ 10.5120/ijca2016909973,
author = { Harkirat Kaur, Shivani Sharma },
title = { Performance Evaluation of Re-Routing based Hybrid ACO-PSO based Routing Algorithm for MANETS },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 13 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number13/24956-2016909973/ },
doi = { 10.5120/ijca2016909973 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:57.997520+05:30
%A Harkirat Kaur
%A Shivani Sharma
%T Performance Evaluation of Re-Routing based Hybrid ACO-PSO based Routing Algorithm for MANETS
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 13
%P 12-15
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless ad-hoc networks is a parent breed to Mobile ad-hoc networks, comprising of many mobile nodes capable of dynamically exchanging data amongst nodes without demanding a centralized infrastructure. Re-routing based Hybrid ACO-PSO based routing algorithm for MANETs have been discussed in this paper and is studied for evaluating its performance. This algorithm is applicable to multi-hop ad-hoc networks with the aim of upgrading the performance of the existing protocol for mobile ad hoc network. The Re-routing based Hybrid strategy is developed and deployed using MATLAB 2013a and the toolbox used is data analysis toolbox. The performance is evaluated by comparing the technique that already exists to the one that is proposed in this paper. The results have shown that the new techniques outperforms the previous technique.

References
  1. Yuan Xue and Klara Nahrstedt : Fault Tolerant Routing in Mobile Ad Hoc Networks . 0-7803-7700-1/03/$17.00 (C) 2003 IEEE
  2. Breed Gary. Wireless ad hoc networks: basic concepts. High Freq Electron 2007:44–6.
  3. Munaretto Anelise, Fonseca Mauro. Routing and quality of service support for mobile ad hoc networks. Comput Networks 2007;51(11):3142–56.
  4. Sabari.A and Dr.K.Duraiswamy : Ant Based Multicast Routing Algorithm with Multiple Constraints for Mobile Adhoc Networks . 2008 International Conference on Security Technology
  5. Karim khazaei, Sadegh Mohammadi and Akbar Momeni : A Fault Tolerant Location Management for MANET . 978-1-4244-4565-3/09/$25.00 ©2009 IEEE
  6. Amri Huda Al, Abolhasan Mehran, Wysocki Tadeusz. Scalability of MANET routing protocols for heterogeneous and homogenous networks. ComputElectr Eng 2010;36(4):752–65.
  7. Ali Zulfiqar, Shahzad. Critical analysis of swarm intelligence based routing protocols in ad-hoc and sensor wireless networks. In: International conference on computer networks and information technology; 2011. p. 287–292.
  8. P.Deepalakshmi, Dr.S.Radhakrishnan
: SOURCE-INITIATED QOS MULTICASTING SCHEME FOR MANETS USING ACO. 978-1-61284-764-1/11/$26.00 ©2011 IEEE
  9. Pi Shangchao, Sun Baolin. Fuzzy controllers based multipath routing algorithm in MANET routing. In: International conference on applied physics and industrial engineering. Part B, vol. 24; 2012. p. 1178–85.
  10. Thanushkodi, Deeba K. Hybrid intelligent algorithm [improved particle swarm optimization (PSO) with ant colony optimization (ACO)] formultiprocessor job scheduling. Sci Res Essays 2012;7(20):1935–53.
  11. Aarti, Dr. S. S. Tyagi. A Study of MANET: Characteristics, Challenges, Applicationand Security Attacks. IJARCSSE Volume 3, Issue 5, May 2013
  12. Cheng Hui, Yang Shengxiang, Cao Jiannong. Dynamic genetic algorithms for the dynamic load balanced clustering problem in mobile ad hoc networks. Expert Syst Appl 2013;40(4):1381–92.
  13. Ejaz Waleed, Manzoor Kamran, Kim Hyung Joo, Jang Byung Tae, Jin Gwang-Ja, Kim Hyung Seok. Two-state routing protocol for maritime multi-hop Wireless networks. Comput Electr Eng 2013;39(6):1854
  14. Issac Woungang, Sanjay Kumar Dhurendher, Mohammad S. Obaidat, Alexander Ferwom , Waqas Shah: An ant-swarm inspired energy efficient ad-hoc on demand routing protocol for mobile ad-hoc networks. 978-1-4673-3122-7/13/$31.00 ©2013 IEEE
  15. R. Kalairasi, Dr. Shridharan: Performance improvement of mobile ad hoc network using particle swarm optimization.. Journal of Computational Information Systems 9: 11 (2013) 4213–4221
  16. Sudarshan D Shirkande,Rambabu A Vatti: ACO based routing algorithms for adhoc network(WSN,MANETs): A Survey. 2013 International Conference on communication systems and network topology
  17. Alexandros Giagkos, Myra S. Wilson : BeeIP – A Swarm Intelligence based routing for wireless ad hoc networks .Information Sciences 265 (2014) 23–35
  18. B. Nancharaiah , B. Chandra Mohan :The performance of hybrid routing intelligent algorithm in a mobile ad-hoc network. Computers and Electrical Engineering 40 (2014) 1255–1264
  19. Mahima Chitkara, Mohd. Waseem Ahmad : Review on MANET: Characteristics, Challenges, Imperatives, and Routing protocols. IJCSMC, Vol. 3, Issue. 2, February 2014, pg.432 – 437
  20. Tarun Varshney, Aishwary Katiyar, Pankaj Sharma :Performance improvement of MANET under DSR protocol using swarm optimization. 978-1-4799-2900-9/14/$31.00 ©2014 IEEE
  21. Vallikannu R , A. George , S.K. Srivatsa: Autonomous localization based energy saving mechanism in indoor MANETs using ACO .1570-8667/© 2014 Elsevier B. V
Index Terms

Computer Science
Information Sciences

Keywords

MANET Hybrid ACO-PSO Ant colony optimization particle swarm optimization