摘要
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.
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 implementation.
出处
《计算机科学》
CSCD
北大核心
2003年第6期84-87,125,共5页
Computer Science
基金
本课题得到国家"九七三"重点基础研究发展规划项目(编号G1999032307)
国家自然科学基金重点项目(编号60135010)
国家自然科学基金项目(编号60073008)
清华大学智能技术和系统国家重点实验室开放课题基金的资助和支持
