Cost-effective base station deployment approach based on artificial immune systems

Authors:
Djalma de Melo Carvalho Filho;Marcelo Sampaio de Alencar
Affiliations:
Federal University of Campina Grande, Campina Grande, Brazil;Federal University of Campina Grande, Campina Grande, Brazil
Venue:
Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
Year:
2008

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Abstract

This work presents a cost-effective base station deployment model based on artificial immune systems. It uses a multi-objective algorithm based on artificial immune systems (MO-AIS) as an optimiser. MO-AIS algorithms are a new class of evolutionary algorithms. The Binary-coded Multi-objective Optimisation Algorithm (BRMOA) is inspired by the clonal selection theory and the immune network theory. In this innovative approach, the network is optimised for high service coverage and low cost. The cost function takes into account user-defined geographical costs and environmental legislation. The optimisation strategy is applied to two realistic scenarios and results are compared.