  We found that models of evolving random networks exhibit dynamic scaling
similar to scaling of growing surfaces. It is demonstrated by numerical
simulations of two variants of the model in which nodes are added as well as
removed [Phys. Rev. Lett. 83, 5587 (1999)]. The averaged size and connectivity
of the network increase as power-laws in early times but later saturate.
Saturated values and times of saturation change with paramaters controlling the
local evolution of the network topology. Both saturated values and times of
saturation obey also power-law dependences on controlling parameters. Scaling
exponents are calculated and universal features are discussed.
