End-to-end delay and Communication cost are the most important metrics in MANET (Mobile Adhoc Network) routing from source to destination. Recent approaches in Swarm intelligence (SI) technique, a local interaction of many simple agents to meet a global goal, prove that it has more impact on routing in MANETs. Ant Colony Optimization (ACO) algorithm uses mobile agents as ants to discover feasible and best path in a network. ACO helps in finding the paths between two nodes in a network and acts as an input to the Particle Swarm Optimization (PSO) technique, a metaheuristic approach in SI. PSO finds the best solution over the particle's position and velocity with the objective of cost and minimum End-to-end delay. This hybrid algorithm exhibits better performances when compared to ACO approach. © 2013 IEEE.
CITATION STYLE
Nancharaiah, B., & Mohan, B. C. (2013). MANET link performance using Ant Colony Optimization and Particle Swarm Optimization algorithms. In International Conference on Communication and Signal Processing, ICCSP 2013 - Proceedings (pp. 767–770). https://doi.org/10.1109/iccsp.2013.6577160
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