Analysis Of The Topological Properties In The Evolution Of Unstructured P2P

P2P is an invention that significantly changed the fashion that people acquire in-formation on the Internet. It eliminates the bottleneck when acquiring information fromservers and improves the efficiency of information dissemination on the Internet. Eventhe life style of human beings has changed because the emergence of P2P. P2P is moreefficient than traditional C/S structure. In P2P, peers who exchange information es-tablish direct connections. All the participating nodes organize into a network for ex-changing of information. There are several applications of P2P, such as grid computing,distributed storage, Web cache, VoIP, media streaming, Web conferencing, content dis-tribution, etc. In P2P, there are no center nodes who manage the whole network. Allthe nodes is responsible to the management of network topology. Because of the inde-pendent operation of nodes, there can be much churn in P2P networks; therefore, theresearch on the topology dynamics can be a reference in the design and evaluation ofP2P protocol.Our research mainly focuses on the topology dynamics on unstructured P2P.Firstly, we studied the evolution of unstructured P2P topology. Based on the mea-surement of P2P, we propose an evolution model for the topology dynamics of unstruc-turedP2P,inwhich, notonlythedynamicsofnodesisconsidered, butalsothedynamicsof connections. Furthermore, the input of the model is the statistical parameters reflect-ing user behaviors in the network. We can analyze the impact of user behaviors on thetopology based on this model. We analyzed the evolution model without considera-tion of the diversity of user behaviors, and give a difference equation of the networkdegree distribution together with its solution. We evaluated our model by simulationand numeric analysis. Both of the simulation and analysis indicate that there are twofactors that affect the network degree distribution; one makes the network degree distri-bution follow power-law distribution, while the other makes it deviate from power-lawdistribution, and the degree of such deviation is affected by user behaviors.Secondly, we modeled a class of service-providing network. Such network is con-sisted of several servers who accomplish parts of the functions and provides servicesfor its remote clients. Under the condition that no nodes depart or join the network, wemodeled the service-providing network by using the evolution model of unstructuredP2P, and give the difference equation of network degree distribution along with its solu-tion. Theresultsofsimulationandanalysisindicatethattheresourcedegreedistribution isPoissondistribution, theaverageofwhichisaffectedbytheresourcerequestingprob-ability and resource distribution probability. The network degree distribution is sum ofseveral Poisson distributions.Lastly, weanalyzedthedynamicsofcommunitiesonGnutella. Basedonthetopol-ogy data set measured during a period of time, we are able to analyze the dynamics ofcommunities on Gnutella by using dynamic community detection algorithm. The re-sults show that communities on Gnutella is not stable, they would always split becauseof the churn of users. Furthermore, the stability of users'community is also very low,users would always change their communities during the evolution of Gnutella.