Open AccessPopularity based network statistical analysis in peer-to-peer application
Author(s) -
Jingxin Wang,
Yue Wang,
Yipeng Li,
Jian Yuan,
Shan Xiu-Ming,
Feng Zhen-Ming,
Yong Ren
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.118901
Subject(s) - popularity , cluster analysis , computer science , workload , peer to peer , cluster (spacecraft) , data mining , resource (disambiguation) , representation (politics) , hierarchical clustering , data science , computer network , machine learning , psychology , social psychology , politics , political science , law , operating system
There are rich statistical characteristics in a peer-to-peer (p2p) network. The more refined statistical characteristics still need further understanding. In this paper we define the popularity threshold of the resource, and abstract the user network based on the popularity threshold to reflect the refined structure characteristics. Through the emprical study of a workload from a dominant peer-to-peer file sharing system, we confirm that the user network based on the popularity threshold has more clear cluster features than the original network. With the popularity threshold of resource increasing, the clustering is more evident. The homoplasy of users within the same cluster is enhanced. The clustering accuracy is inproved. Furthermore, in this paper we extract the cluster fingerprints which can provide a high representation accuracy in low dimensions.