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Toward a dynamically balanced cluster oriented DHT

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Detalhes bibliográficos
Resumo:In this paper, we present a model for a cluster oriented Distributed Hash Table (DHT). It introduces software nodes, virtual nodes and partitions as high level entities that, in conjunction with the definition of a certain number of in variants, provide for the balancement of a DHT across a set of heterogeneous cluster nodes. The model has the following major features: a) the share of the hash table handled by each cluster node is a function of its enrollment level in the DHT; b) the enrollment level of a cluster node in the DHT may change dynamically; c) cluster nodes are allowed to dynamically join or leave the DHT. A preliminary evaluation proved that the quality of the balancement of partitions of the hash table across the cluster, measured by the stan dard deviation with relation to the ideal average, surpass the one achieved by using another well known approach.
Autores principais:Rufino, José
Outros Autores:Pina, António; Alves, Albano; Exposto, José
Assunto:Cluster computing Distributed hash tables Partitioning strategies
Ano:2004
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:In this paper, we present a model for a cluster oriented Distributed Hash Table (DHT). It introduces software nodes, virtual nodes and partitions as high level entities that, in conjunction with the definition of a certain number of in variants, provide for the balancement of a DHT across a set of heterogeneous cluster nodes. The model has the following major features: a) the share of the hash table handled by each cluster node is a function of its enrollment level in the DHT; b) the enrollment level of a cluster node in the DHT may change dynamically; c) cluster nodes are allowed to dynamically join or leave the DHT. A preliminary evaluation proved that the quality of the balancement of partitions of the hash table across the cluster, measured by the stan dard deviation with relation to the ideal average, surpass the one achieved by using another well known approach.