Exact Average Degree Model for Stochastic Network Simulation
Kejian Liu · Computer Integrated Manufacturing Systems · 2004
To remain the consistency of network simulation model and real network, an algorithm to create stochastic network was proposed. Firstly, the stochastic network nodes were produced according to their regional density and the core nodes and special functional (i.e. OVERLAY node) nodes were selected. Second, the new probability connectivity formula was deduced. Then, the classification and restriction strategies of increasing degree were discussed. Finally, the fast connectivity strategy of stochastic network was presented. Based on above algorithm, the model of exact average degree (EAD) for stochastic network simulation was built. Having simulated and analyzed the performances of the model, it is indicated that this model is universal and can be customized. Compared with existing algorithms, the proposed algorithm is well convergent and has linear approach to simulated real network.