An information theory approach to network evolution models

Abstract A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called chain, a stationary ergodic stochastic process. Therefore, asymptotic equipartition property can applied to it. The model’s entropy rate typical sequences are also explored. Extracting particular from methods simulate in continuous time domain discussed. Additionally, Erd?s–Rényi chain as subset our with additional its distribution matching random graph model. distributions nodes graphs calculated for this alongside rate. simulation results at end article back up theorems values.