In this paper,the acceleratingly growing network model with intermittent processes is proposed.In thegrowing network,there exist both accelerating and intermittent processes.The network is grown from the number ofnode...In this paper,the acceleratingly growing network model with intermittent processes is proposed.In thegrowing network,there exist both accelerating and intermittent processes.The network is grown from the number ofnodes m<sub>o</sub> and the number of links added with each new node is a nonlinearly increasing function m+aN<sup>β</sup>（t）f（t）,whereN（t） is the number of nodes present at time t.f（t） is the periodic and bistable function with period T,whose values are1 and 0 indicating accelerating and intermittent processes,respectively.Here we denote the ratio r of acceleration timeto whole one.We study the degree distribution p（k） of the model,focusing on the dependence of p（k） on the networkparameters τ,T,m,α,N,and β.It is found that there exists a phase transition point,k<sub>c</sub> such that if k【k<sub>c</sub>,then p（k）obeys a power-law distribution with exponent -γ<sub>1</sub>,while if k】k<sub>c</sub>,then p（k） exhibits a power-law distribution withexponent-γ<sub>2</sub>.Moreover,the exponents γ<sub>1</sub> and γ<sub>2</sub> are independent of τ,T,m,a,and N,while they depend only onthe parameter β.More interesting,the phase transition point is described by k<sub>c</sub>=aN<sup>β</sup>,which is equal to the value atwhich p（k） is maximum in GM model.展开更多
基金The project supported by National Natural Science Foundation of China under Grant Nos.70571017 and 10247005the Innovation Project of Guangxi Graduate Education under Grant No.2006106020809M36
文摘In this paper,the acceleratingly growing network model with intermittent processes is proposed.In thegrowing network,there exist both accelerating and intermittent processes.The network is grown from the number ofnodes m<sub>o</sub> and the number of links added with each new node is a nonlinearly increasing function m+aN<sup>β</sup>（t）f（t）,whereN（t） is the number of nodes present at time t.f（t） is the periodic and bistable function with period T,whose values are1 and 0 indicating accelerating and intermittent processes,respectively.Here we denote the ratio r of acceleration timeto whole one.We study the degree distribution p（k） of the model,focusing on the dependence of p（k） on the networkparameters τ,T,m,α,N,and β.It is found that there exists a phase transition point,k<sub>c</sub> such that if k【k<sub>c</sub>,then p（k）obeys a power-law distribution with exponent -γ<sub>1</sub>,while if k】k<sub>c</sub>,then p（k） exhibits a power-law distribution withexponent-γ<sub>2</sub>.Moreover,the exponents γ<sub>1</sub> and γ<sub>2</sub> are independent of τ,T,m,a,and N,while they depend only onthe parameter β.More interesting,the phase transition point is described by k<sub>c</sub>=aN<sup>β</sup>,which is equal to the value atwhich p（k） is maximum in GM model.
