TY - GEN
T1 - Community detection in weighted networks
T2 - 11th IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
AU - Lu, Zongqing
AU - Wen, Yonggang
AU - Cao, Guohong
PY - 2013/7/18
Y1 - 2013/7/18
N2 - Community detection is an important issue due to its wide use in designing network protocols such as data forwarding in Delay Tolerant Networks (DTN) and worm containment in Online Social Networks (OSN). However, most of the existing community detection algorithms focus on binary networks. Since most networks are weighted such as social networks, DTN or OSN, in this paper, we address the problems of community detection in weighted networks and exploit community for data forwarding in DTN and worm containment in OSN. We propose a novel community detection algorithm, and then introduce two metrics called intra-centrality and inter-centrality, to characterize nodes in communities. Based on these metrics, we propose an efficient data forwarding algorithm for DTN and an efficient worm containment strategy for OSN. Extensive trace-driven simulation results show that the data forwarding algorithm and the worm containment strategy significantly outperform existing works.
AB - Community detection is an important issue due to its wide use in designing network protocols such as data forwarding in Delay Tolerant Networks (DTN) and worm containment in Online Social Networks (OSN). However, most of the existing community detection algorithms focus on binary networks. Since most networks are weighted such as social networks, DTN or OSN, in this paper, we address the problems of community detection in weighted networks and exploit community for data forwarding in DTN and worm containment in OSN. We propose a novel community detection algorithm, and then introduce two metrics called intra-centrality and inter-centrality, to characterize nodes in communities. Based on these metrics, we propose an efficient data forwarding algorithm for DTN and an efficient worm containment strategy for OSN. Extensive trace-driven simulation results show that the data forwarding algorithm and the worm containment strategy significantly outperform existing works.
UR - http://www.scopus.com/inward/record.url?scp=84880120943&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880120943&partnerID=8YFLogxK
U2 - 10.1109/PerCom.2013.6526730
DO - 10.1109/PerCom.2013.6526730
M3 - Conference contribution
AN - SCOPUS:84880120943
SN - 9781467345750
T3 - 2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
SP - 179
EP - 184
BT - 2013 IEEE International Conference on Pervasive Computing and Communications, PerCom 2013
Y2 - 18 March 2013 through 22 March 2013
ER -