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A model for heterogeneous networks management and performance evaluation

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Detalhes bibliográficos
Resumo:In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.
Autores principais:Serrador, António
Outros Autores:Correia, Luís M.
Assunto:CRRM RRM Cost function Heterogeneous networks
Ano:2008
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso restrito
Instituição associada:Instituto Politécnico de Lisboa
Idioma:inglês
Origem:Repositório Científico do Instituto Politécnico de Lisboa
Descrição
Resumo:In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.