Research Article
Load Balancing Using Hybrid ACO - Random Walk Approach
@INPROCEEDINGS{10.1007/978-3-642-32615-8_39, author={Neha Bhatia and Rohan Kundra and Anurag Chaurasia and Satish Chandra}, title={Load Balancing Using Hybrid ACO - Random Walk Approach}, proceedings={6th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems}, proceedings_a={BIOADCOM}, year={2012}, month={10}, keywords={Load Balancing Ant Colony Optimization Random Walk Routing Traditional Routing cover access time}, doi={10.1007/978-3-642-32615-8_39} }- Neha Bhatia
Rohan Kundra
Anurag Chaurasia
Satish Chandra
Year: 2012
Load Balancing Using Hybrid ACO - Random Walk Approach
BIOADCOM
Springer
DOI: 10.1007/978-3-642-32615-8_39
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.