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A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 72 - Number 15 |
| Year of Publication: 2013 |
| Authors: Mahendra Pratap Panigrahy, Paramjeet Kaur |
10.5120/12570-8958
|
Mahendra Pratap Panigrahy, Paramjeet Kaur . A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning. International Journal of Computer Applications. 72, 15 ( June 2013), 15-19. DOI=10.5120/12570-8958
Abstract
The mechanism of route search problem is applied to various engineering fields. The various researches for the dynamic routing only revile the shortest path from source to destination but not vice versa. Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behavior is avoided. Several approaches have been integrated with ACO to improve its performance for DOPs. The main objective of this work is to search out the least-time-cost route in a variable-edge-weight graph. It can find multiple transmission paths from sources to the goal by parallel search. We introduce time-dependent pheromones and feedback path model as two heuristic factors to improve the basic ACO. Finally, this proposed heuristic algorithm is verified to be steady-going by repeated testing [1]. Ant Colony Optimization Technique has been applied in different network models with different number of nodes and structure to find the shortest path with optimum throughput. The simulation results show that the proposed dynamic ACO algorithm can effectively reduce time cost by avoiding the dynamic congestion areas. The experimental results show that the algorithm is more effective than the existing ones and it improves the Quality of Service (QoS) [13[14][15].
References
- S. Goss, S. Aron, J. L. Deneubourg, and J. M. Pasteels. Self-organized shortcuts in the Argentine ant. Naturwissenschaften, 76:579–581, 1989.
- C. Gui and P. Mohapatra. SHORT: Self-healing and optimizing routing techniques for mobile adhoc networks. In Proceedings of MobiHoc, 2003.
- M. Gunes, ¨ U. Sorges, and I. Bouazizi. ARA - the ant-colony based routing algorithm for MANETS. In Proceedings of the ICPP International Workshop on Ad Hoc Networks (IWAHN), 2002.
- M. Heissenbuttel ¨ and T. Braun. Ants-based routing in large scale mobile ad-hoc networks. In Kommunikation in verteilten System (KiVS03), March 2003.
- D. Johnson and D. Maltz. Mobile Computing, chapter Dynamic Source Routing in Ad Hoc Wireless Networks, pages 153–181. Kluwer, 1996.
- P. Deepalakshmi and Dr. S. Radhakrishnan, "Ant Colony Based QoS Routing Algorithm For Mobile Ad Hoc Networks," International Journal of Recent Trends in Engineering, Vol. 1, No. 1, May 2009.
- Ajay C Solai Jawahar, "Ant Colony Optimization for Mobile Ad-hoc Networks," Department of Electrical Engineering, Rutgers.
- Rajeshwar Singh, D K Singh and Lalan Kumar, "Ants Pheromone for Quality of Service Provisioning In Mobile Adhoc Networks," International Journal of Electronic Engineering Research, ISSN 0975 – 6450, Vol. 2 , Number 1, pp. 101–109, 2010.
- D. Camara ˆ and A. Loureiro. Gps/ant-like routing in ad hoc networks. Telecommunication Systems, 18(1–3):85–100, 2001.
- T. Camp, J. Boleng, and V. Davies. A survey of mobility models for ad hoc network research. Wireless Communications & Mobile Computing: Special issue on Mobile Ad Hoc Networking: Research, Trends and Applications, 2002.
- R. Schoonderwoerd, O. Holland, J. Bruten, and L. Rothkrantz. Ant-based load balancing in telecommunications networks. Adaptive Behavior, 5(2):169{207, 1996.
- C. -C. Shen and S. Rajagopalan. Protocol-independent multicast packet delivery improvement service for mobile ad hoc networks. Journal of Computer Science, 5(2):210{227, 2007.
- E. Sigel, B. Denby, and S. Le He_arat-Mascle. Application of ant colony optimization to adaptive routing in a LEO telecommunications satellite network. Annals of Telecommunications, 57(5{6):520{539, 2002.
- K. M. Sim and W. H. Sun. Ant colony optimization for routing and load-balancing: Survey and new directions. IEEE Transactions on Systems, Man, and Cybernetics {Part A, 33 (5):560{572, 2003.
- D. Subramanian, P. Druschel, and J. Chen. Ants and reinforcement learning: A case study in routing in dynamic networks. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pages 832{838, San Francisco, CA, 1997. Morgan Kaufmann.
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