3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems

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  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4696,
        author={Djalma de Melo Carvalho  Filho and Marcelo Sampaio de Alencar},
        title={Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems},
        proceedings={3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
        publisher={ICST},
        proceedings_a={BIONETICS},
        year={2010},
        month={5},
        keywords={Base station deployment; optimisation; artificial immune systems.},
        doi={10.4108/ICST.BIONETICS2008.4696}
    }
    
  • Djalma de Melo Carvalho Filho
    Marcelo Sampaio de Alencar
    Year: 2010
    Cost-effective Base Station Deployment Approach Based on Artificial Immune Systems
    BIONETICS
    ICST
    DOI: 10.4108/ICST.BIONETICS2008.4696
Djalma de Melo Carvalho Filho1,*, Marcelo Sampaio de Alencar1,*
  • 1: Federal University of Campina Grande, Av. Aprígio Veloso, 882, CEP 58109-970 Campina Grande, Brazil Tel: 558333101578
*Contact email: djalmacarvalho@uol.com.br, malencar@iecom.org.br

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.