We design and implement a novel information self-organization model based on Generalized Cellular Automata (GCA), to accomplish network information content self-organization employing the idea of swarm intelligence. Through constructing correspondent cell rules and the mapping of complex network environment to our GCA, reasonable distribution of network information from different information sources can be achieved on different notes according to dynamic variation of local network circumstances. Simulation experiment results show many advantages of our methodology over present approaches in terms of efficiency, adaptability, reliability, and easy hardware imple- mentation.
