Advertisement

Optimizing Routes in Mobile Ad Hoc Networks Using Genetic Algorithm and Ant Colony Optimization

  • Pankaj Uttam Vidhate
  • R. S. Bichkar
  • Yogita Wankhade
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 379)

Abstract

A network formed with the collaboration of mobile nodes which can communicate among themselves is called as Mobile Ad hoc NETwork (MANET). These networks are infrastructure less in nature causing the mobile nodes to act like routers and which in turn forward the packets from the source node to the destination node. Different protocols have been used to maintain connectivity between mobile nodes. Continuous movement of nodes, radio transmission and low battery power of mobile nodes can lead to break the connectivity between nodes. Thus, the performance of network may depend upon the protocol used for routing purpose. To measure quality of service (QoS) of the network, various factors can be used like ratio of packet delivery, end to end delay, control and routing overhead, and distance in terms of nodes present between the source and destination nodes. To search an optimized path between source and destination node pair, different optimization methods are applied. In this paper, the proposed algorithm uses ant colony optimization (ACO) Technique to explore most outstanding feasible paths in collaboration with genetic algorithm (GA) which assists to give globally optimal solution among feasible paths generated by the ACO. The experiments carried out use the AODV protocol with GAAPI protocol in terms of packet delivery, delay required in end to end communication and energy consumption.

Keywords

MANET QoS GAAPI ACO AODV 

References

  1. 1.
    Barolli, A., Takizawa, M., Xhafa F.: Application of genetic algorithms for QoS routing in mobile ad hoc networks., pp. 250–259. IEEE (BWCCA) (2010)Google Scholar
  2. 2.
    Sharma, A., Sinha, M.: Influence of crossover and mutation on the behavior of genetic algorithms in mobile ad-hoc networks. In: International Conference on Computing for Sustainable Global Development, pp. 895–899. IEEE (2014)Google Scholar
  3. 3.
    Abdullah, J.: Multi-objectives GA-based QOS routing protocol for mobile ad hoc network. In: IJGDC, pp. 57–68 (2010)Google Scholar
  4. 4.
    Afridi, M.I.: Selection and ranking of optimal routes through genetic algorithm in a cognitive routing system for mobile ad hoc network. In: ISCID, pp. 507–510. IEEE (2012)Google Scholar
  5. 5.
    Abdullah, J., Ismail, M.Y., Cholan, N.A., Hamzah, S.A.: GA-based QoS route selection algorithm for mobile ad-hoc networks. In: NCTT-MCP, pp. 339–343. IEEE (2008)Google Scholar
  6. 6.
    Siwach, V., Singh, Y., Seema, Barak, D.: An approach to optimize QoS routing protocol using genetic algorithm in MANET. In: IJCSMS, pp. 149–153 (2012)Google Scholar
  7. 7.
    Sardar, A., Singh, A., Sahoo, R., Majumder, R., Sing, R., Sarkar, R.: An efficient ant colony based routing algorithm for better quality of services in MANET. In: ICT & CI, pp. 233–240. Springer (2014)Google Scholar
  8. 8.
    Kolavali, S., Bhatnagar, S.: Ant colony optimization algorithms for shortest path problems. In: NET-COOP, pp. 37–44. Springer (2008)Google Scholar
  9. 9.
    Sensarma, D., Majumder, K.: A comparative analysis of the ant based systems for QoS routing in MANET. In: International Conference, SNDS, pp. 485–496. Springer (2012)Google Scholar
  10. 10.
    Yang, S., Cheng, H., Wang, F.: Genetic Algorithms With immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks. In: Transactions on Systems, Man, and Cybernetics, pp. 52–63. IEEE (2010)Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Pankaj Uttam Vidhate
    • 1
  • R. S. Bichkar
    • 1
  • Yogita Wankhade
    • 1
  1. 1.G.H. Raisoni College of Engineering & ManagementPuneIndia

Personalised recommendations