Ant Colony Optimization Approach to Communications Networks Design

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2. About ACO in Comm.. ObjectiveResearch Info.AbstractAnt Colony OptimizationSummaryAppendix. 3. Objective. To study current Ant Colony Optimization algorithms and existing routing protocols. This is to identify the various types of problems in communications networks design (especially routing

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Ant Colony Optimization Approach to Communications Networks Design

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1. 1 Ant Colony Optimization Approach to Communications Networks Design Monday, July 30, 2012 By Bau Yoon Teck [email protected] http://pesona.mmu.edu.my/~ytbau/ MMU FIT COE for CAIIC

2. 2 About ACO in Comm. Objective Research Info. Abstract Ant Colony Optimization Summary Appendix

3. 3 Objective To study current Ant Colony Optimization algorithms and existing routing protocols. This is to identify the various types of problems in communications networks design (especially routing) that Ant Colony Optimization (ACO) can tackle. To apply ACO algorithms for the construction of degree-constrained communications networks. To perform routing in degree-constrained communications network using ACO and its hybrid versions. To compare the performance of conventional as well as existing ACO routing techniques against that of the proposed algorithms.

4. 4 Research Info. Type of Research: Applied /Fundamental Beneficiaries of Project: Researchers and companies involved in communications networks design Product/Services: Software Tools Researchers: Mr. Bau Yoon Teck Source of Funding: nil Status of Project: Ongoing

5. 5 Abstract Ant Colony Optimization (ACO) is an algorithm for discrete optimization and multiagent meta-heuristic approach to difficult NP-hard combinatorial optimization problems and routing in communications networks. The inspiring source of ACO is the pheromone trail laying and following behaviour of real ants, which use pheromones as a communication medium. We apply ACO algorithms to routing problems in communications networks under static and dynamic conditions. This study is divided into three parts. The first part aims to identify various existing routing protocols and compare their performance to that of the ACO. The second part of this research involves formulating and applying the ACO algorithms to construct degree-constrained communications networks. The ACO routing will then be applied on the constructed networks, taking into consideration different traffic conditions. The final part of the study will focus on designing hybrid ACO routing protocols that incorporates genetic algorithms (GAs) and reinforcement learning.

6. 6 Ant Colony Optimization

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