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Reseach Article

Performance Analysis of a Telecommunication Network using Swarm Intelligence

by Karuna Rani, Meenu Vijarania
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 13
Year of Publication: 2013
Authors: Karuna Rani, Meenu Vijarania
10.5120/13580-0339

Karuna Rani, Meenu Vijarania . Performance Analysis of a Telecommunication Network using Swarm Intelligence. International Journal of Computer Applications. 78, 13 ( September 2013), 1-5. DOI=10.5120/13580-0339

@article{ 10.5120/13580-0339,
author = { Karuna Rani, Meenu Vijarania },
title = { Performance Analysis of a Telecommunication Network using Swarm Intelligence },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 13 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number13/13580-0339/ },
doi = { 10.5120/13580-0339 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:26.778893+05:30
%A Karuna Rani
%A Meenu Vijarania
%T Performance Analysis of a Telecommunication Network using Swarm Intelligence
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 13
%P 1-5
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Swarm Intelligence, a mutant of biological swarms, exhibits numerous powerful features which are described in communication networks. With the increase in size and complexity of network, performance analysis is becoming difficult. With scalability of network, it becomes difficult to manage the route and indicate which one is the best. The intent of this paper is to find optimal path for routing of calls in a telecommunication network and achieve Load Sharing. For finding optimal path, the pheromone laying and sensing property of natural swarms is used. In this research work we present a simulated network model that uses artificial ants and simulated pheromone for finding optimal path from source to destination. Next node selection is done on the basis of local pheromone distribution and pheromone updation takes place based on the congestion encountered on the node. Simulation results using ACO mode will be compared with non-ACO mode using graphs.

References
  1. http://www. sce. carleton. ca/netmanage/tony/swarm. html
  2. http://www. scholarpedia. org/article/Swarm_intelligence.
  3. www. slideserve. com/yael/bio-inspired-algorithms-in- robotics
  4. Marco Dorigo, Mauro Birattari, and Thomas St¨utzle Universit ´ e Libre de Bruxelles, Belgium 28 IEEE Computational Intelligence Magazine | November 2006 1556-603X/06©2006IEEE.
  5. Dorigo et al, M. Dorigo, V. Maniezzo, and A. Colorni. ," Positive feedback as a search strategy" Technical Report 91-016, Dipartimento di Elettronica, Politecnico di Milano, Italy,1991.
  6. Beckers, R. , Holland, O. E. , & Deneubourg, J. L. , " From local actions to global tasks:stigmergy and Collective Robotics". In R. A. Brooks, & P. Maes(Eds. ) Artificial Life IV, Cambridge, MIT Press. p. 181-189, 1994.
  7. http://www. umsl. edu/~joshik/msis480/chapt07. htm
  8. http://www. techterms. com/definition/loadbalancing
  9. Behrouz A. Forouzan, Data Communication and Networking, 4th ed. , McGraw-Hill,2011.
  10. Richard S. Sutton and Andrew G. Barto. " Reinforcement Learning: An Introduction", Cambridge, MA: MIT Press, 1998
  11. System Simulation with Digital Computer: Books by Nar Singh Deon.
  12. Schoonderwoerd et al 97 R. Schoonderwoerd, O. Holland, J. Bruten, "Ant-like agents for load balancing in telecommunications networks". Hewlett-Packard Laboratories, Bristol-England, 1997
  13. D. Subramanian, P. Druschel, and J. Chen. (1997), " Ants and reinforcement learning: A case study in routing in dynamic networks". In Proceedings of IJCAI-97, International Joint Conference on Artificial Intelligence, pp. 832–838. Morgan Kaufmann, 1997.
  14. B. Baran and R. Sosa. , " A new approach for AntNet routing". In Proceedings of the 9th International Conference on Computer Communications Networks, Las Vegas, USA, 2000. .
  15. 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, September 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Swarm Intelligence Ant Colony Optimization(ACO) Mobile Agents Multiple Ant Colony Optimization(MACO) Set Covering Problem(SCP).