Optimized Routing in Cognitive Networks using Ant Colony Algorithm

Nadia Tabassum, Tahir Alyas


Tactical communication through network faces various operational scenarios having complexity, heterogeneity, and reliability requirements for network optimization. Learning from the heterogeneous network environment, in order to adjust the network settings, is an essential requirement for providing efficient communication services in such complex and dynamic environments. Routing algorithms with learning capability for routing choice quality could determine wireless network efficiency and is a hot research area now a days.Cognitive networks are capable of reasoning and learning. They can energetically adapt to varying network conditions in order to optimize end-to-end performance and utilize best routing to overcome the network loads. In this paper, we are focusing on the feasibility and effectiveness of the ant colony algorithm in wireless routing. The Ant colony algorithm is applied to wireless cognitive network, to obtain the performance effect of wireless sensor network routing protocol under the different network nodes.

Keywords: Cognitive Network, Wireless Network, Routing Protocol

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ISSN (Paper)2224-610X ISSN (Online)2225-0603

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