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.
Nowadays, bandwidth allocation schemes in a TCP/IP or ATM network are congestion avoidance oriented. Few scheme has taken global optimization into account, for global optimization problem can not be easily solved by conventional mathematical method due to the complexity and large-scale of massive information system, such as Internet. We present a novel bandwidth allocation scheme based on generalized cellular automaton (GCA). Firstly we introduce how to map network topology into GCA model, then we propose how cells and macro cells interact in our solution. Our simulation results show the scheme leads to global optimization rapidly.
