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Load Balancing Using Hybrid ACO - Random Walk Approach

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Abstract

Telecommunication and network systems have become more complex in recent years. Routing and optimal path finding are some of the important network problems. Traditional routing methods are not capable to satisfy new routing demands. Swarm intelligence is a relatively new approach to problem solving which provides a basis with which it explores problem solving without providing a global model. A Random Walk approach is similar to a drunkard moving along a sidewalk from one lamp post to another where each step is either backwards or forwards based on some probability. In this paper a hybrid algorithm is proposed that combines Ant Colony Optimization algorithm and Random Walk. The overall time complexity of the proposed model is compared with the existing approaches like distance vector routing and Link State Routing. The new method is found to be better than the existing routing methods in terms of complexity and consistency.

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Bhatia, N., Kundra, R., Chaurasia, A., Chandra, S. (2012). Load Balancing Using Hybrid ACO - Random Walk Approach. In: Suzuki, J., Nakano, T. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32615-8_39

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  • DOI: https://doi.org/10.1007/978-3-642-32615-8_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32614-1

  • Online ISBN: 978-3-642-32615-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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