Network clustering algorithms are typically based only on the topology information of the network. In this paper, we introduce traffic as a quantity representing the intensity of the relationship among nodes in the network, regardless of their connectivity, and propose an evolutionary clustering algorithm, based on the application of genetic operators and capable of exploiting the traffic information. In a comparative evaluation based on synthetic instances and two real world datasets, we show that our approach outperforms a selection of well established evolutionary and non-evolutionary clustering algorithms.
A traffic-based evolutionary algorithm for network clustering / Maurizio, Naldi; Sancho Salcedo, Sanz; Leopoldo Carro, Calvo; Laura, Luigi; Antonio Portilla, Figueras; Giuseppe F., Italiano. - In: APPLIED SOFT COMPUTING. - ISSN 1568-4946. - STAMPA. - 11:13(2013), pp. 4303-4319. [10.1016/j.asoc.2013.06.022]
A traffic-based evolutionary algorithm for network clustering
LAURA, Luigi;
2013
Abstract
Network clustering algorithms are typically based only on the topology information of the network. In this paper, we introduce traffic as a quantity representing the intensity of the relationship among nodes in the network, regardless of their connectivity, and propose an evolutionary clustering algorithm, based on the application of genetic operators and capable of exploiting the traffic information. In a comparative evaluation based on synthetic instances and two real world datasets, we show that our approach outperforms a selection of well established evolutionary and non-evolutionary clustering algorithms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
