A Fast and Scalable Re-routing Algorithm based on Shortest Path and Genetic Algorithms J. Lee, J. Yang Jungkyu Lee

This paper presents a fast and scalable re-routing algorithm that adapts to dynamically changing networks. The proposed algorithm, DGA, integrates Dijkstra’s shortest path algorithm with the genetic algorithm. Dijkstra’s algorithm is used to define the predecessor array that facilitates the initialization process of the genetic algorithm. Then the genetic algorithm keeps finding the best routes with appropriate genetic operators under dynamic traffic situations. Experimental results demonstrate that DGA produces routes with less traveling time and computational overhead than pure genetic algorithm-based approaches as well as Dijkstra’s algorithm in largescale routing problems

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets