Recursive Ant Colony Optimization Routing in Wireless Mesh Network

  • J. Amudhavel
  • S. Padmapriya
  • R. Nandhini
  • G. Kavipriya
  • P. Dhavachelvan
  • V. S. K. Venkatachalapathy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


The ant colony optimization algorithm is used to find the optimal path based on the behavior of an ant while searching a food. It will communicate with other ants using the pheromone to find the best solution. In this paper, we introduce recursive ant colony optimization (RACO) in the wireless mesh network. This technique is used to subdivide a large network into smaller networks and based on the network, the shortest path is found in each subproblem, and finally it is combined to generate an optimal path for the network. In each subproblem, the iteration is performed recursively to obtain the shortest path in that subproblem. In our paper, we use recursive ant colony to reduce redundancy in connection and so the data will transfer in less time effectively. RACO is used to find best solutions more accurate than the other ant colony systems. Isolation of a subproblem is reduced in RACO.


Ant colony optimization Recursive ant colony optimization Wireless mesh network Orthodox client 


  1. 1.
    Bahreininejad, L.A., Hesamfar, P.: Subdomain generation using emergent ant colony optimization. Comput. Struct. 84(28), 1719–1728 (2006). ISSN:0045-7949Google Scholar
  2. 2.
    Amudhavel, J., Vengattaraman, T., Basha, M.S.S., Dhavachelvan, P.: Effective maintenance of replica in distributed network environment using DST. In: International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom) 2010, pp. 252, 254, 16–17 Oct. 2010. doi: 10.1109/ARTCom.2010.97
  3. 3.
    Ling, C., Lingjun, Z., Chen, Y.: An efficient ant colony algorithm for multiple sequences alignment. In: Third International Conference on, Natural Computation, 2007. ICNC 2007, vol. 4, pp. 208, 212, 24–27 Aug. 2007Google Scholar
  4. 4.
    Vengattaraman, T., Abiramy, S., Dhavachelvan, P., Baskaran, R.: An application perspective evaluation of multi-agent system in versatile environments. Int. J. Expert Syst Appl Elsevier (2011)(3), 1405–1416Google Scholar
  5. 5.
    Manju, A., Sharma, V.K.: Ant colony approach to constrained redundancy optimization in binary systems. Appl. Math. Modell. 34(4), 992–1003 (2010). ISSN:0307-904XGoogle Scholar
  6. 6.
    Dhavachelvan, P., Uma,G.V.: Multi-agent based integrated framework for intra class testing of object-oriented software. In: 18th ISCIS 2003, Springer Verlag—Lecture Notes in Computer Science (LNCS), vol. 2869, pp. 992–999. ISSN:0302-9743Google Scholar
  7. 7.
    Raju, R., Amudhavel, J., Pavithra, M., Anuja, S., Abinaya, B.: A heuristic fault tolerant MapReduce framework for minimizing makespan in hybrid cloud environment. In: International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE) 2014, pp. 1, 4, 6–8 March 2014. doi: 10.1109/ICGCCEE.2014.6922462
  8. 8.
    Guisong, L., Zhao, Q., Hong Q., Luping, J.: Computing k shortest paths using modified pulse-coupled neural network. Neurocomputing 149 Part C, pp. 1162–1176 (2015). ISSN:0925-2312Google Scholar
  9. 9.
    Ebrahimipur, V., Shabani, A.: Optimization multi-stateseries weighted k-out-of-n systems by ant colony algorithm. In: IEEE International Conference on, Industrial Engineering and Engineering Management, 2009. IEEM 2009, pp. 281, 285, 8–11 Dec 2009Google Scholar
  10. 10.
    Yasuhiro, U., Takuji, T.: Rapid topology design based on shortest path betweenness for virtual network construction. IERI Procedia 10, pp. 105–111 (2014). ISSN:2212-6678Google Scholar
  11. 11.
    Raju, R., Amudhavel, J., Kannan, N., Monisha, M.: A bio inspired energy-aware multi objective chiropteran algorithm (EAMOCA) for hybrid cloud computing environment. In: International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE) 2014, pp. 1, 5, 6–8 March 2014. doi: 10.1109/ICGCCEE.2014.6922463
  12. 12.
    Trevizan, F.W., Veloso, M.M.: Depth-based short-sighted stochastic shortest path problems. Artificial Intell. 216, 179–205 (2014). ISSN:0004-3702Google Scholar
  13. 13.
    Hua, J., Liping, Z., Yanxiu, L., Min, Z.: Multi constrained QOS routing optimization of wireless mesh network based on hybrid genetic algorithm. In: 2010 International Conference on, Intelligent Computing and Integrated Systems (ICISS), pp. 862, 865, 22–24 Oct. 2010Google Scholar
  14. 14.
    Raju, R., Amudhavel, J., Kannan, N., Monisha, M.: Interpretation and evaluation of various hybrid energy aware technologies in cloud computing environment—a detailed survey. In: International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE) 2014, pp. 1,3, 6–8 March 2014. doi: 10.1109/ICGCCEE.2014.6922432
  15. 15.
    Venkatesan, S., Dhavachelvan, P., Chellapan, C.: Performance analysis of mobile agent failure recovery in e-service applications. Int. J. Comput. Stand. Interf. 32(1–2), 38–43. ISSN:0920-5489Google Scholar
  16. 16.
    Bokhari, F.: Channel assignment and routing in multiradio wireless mesh networks using smart ants. 2011 IEEE International Conference on, Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 403, 404, 21–25 March 2011Google Scholar
  17. 17.
    Gupta, D.K., Arora, Y., Singh, U.K., Gupta, J.P.: Recursive ant colony optimization for estimation of parameters of a function. In: 2012 1st International Conference on Recent Advances in Information Technology (RAIT), pp. 448,454, 15–17 March 2012Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • J. Amudhavel
    • 1
  • S. Padmapriya
    • 1
  • R. Nandhini
    • 1
  • G. Kavipriya
    • 1
  • P. Dhavachelvan
    • 2
  • V. S. K. Venkatachalapathy
    • 3
  1. 1.Department of Computer Science and EngineeringSMVECPondicherryIndia
  2. 2.Department of CSEPondicherry UniversityPondicherryIndia
  3. 3.Department of Mechanical EngineeringSMVECPondicherryIndia

Personalised recommendations