Uma Política de Inserção de Conteúdo baseada na Correlação entre Medidas de Centralidade para Redes Centradas em Conteúdo
Abstract
In-network caching is a key feature of Information Centric Networks (ICN). Choosing the nodes where content should be cached has been a great challenge for designing caching policies in ICN. A good way of doing this is by network centrality measures, which describe the importance of a node regarded to a feature. However, the large number of existing centrality measures poses a challenge to select the one for choosing the caching nodes. Moreover, it is unknown whether the selected measure will produce a high performance in different scenarios, because of its topological structure dependency. Because of that, a good way is to consider their correlation in order to select the nodes. In this work, we propose a caching policy for ICN based on the correlation of network centrality measures. This correlation is obtained through Pearson's correlation coefficient so that the strong or very strongly correlated ones are picked for selecting the caching nodes. Through simulation and using real backbone topologies, our proposal outperformed the other evaluated caching policies in terms of cache hits and average latency time.
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