New strategies based on multithreading methodology in implementing ant colony optimization schemes for improving resource management in large scale wireless communication systems

A great challenge in large scale wireless networks is the resource management adaptability to dynamic network traffic conditions, which can be formulated as a discrete optimization problem. Several approaches such as genetic algorithms and multi agent techniques have been applied so far in the literature for solving the channel allocation problem focusing mainly on network base-stations representation. A very promising computational intelligence technique known as ant colony optimization which constitutes a special form of swarm intelligence has been used for solving routing problems. This approach has been introduced by the authors for improving channel allocation in large scale wireless networks, focusing on network procedures as the basic model unit and not on network nodes as so far reported in the literature. In this paper, a novel channel allocation algorithm based on ant colony optimization and multi agents is thoroughly analyzed as well as important implementation issues based on the multi agent and multi threading concepts are developed. Finally, the experimental simulation results show clearly the impact of the proposed system for improving the channel allocation performance in generic large scale wireless communication systems.