Inspired by swarm intelligence observed in social species, the artificial self-organized networking (SON) systems are expected to exhibit some intelligent features (e.g., flexibility, robustness, decentralized control, and self-evolution, etc.) that may have made social species so successful in the biosphere. Self-organized networks with swarm intelligence as one possible solution have attracted a lot of attention from both academia and industry. In this tutorial, we first different aspects of bio-inspired mechanisms and examine various algorithms (e.g., pulse-coupled oscillators (PCO)-based synchronization, ant- and/or bee-inspired cooperation and division of labor, immune systems inspired network security and Ant Colony Optimization (ACO)-based multipath routing) that have been applied to artificial SON systems. Then, we give some open research issues in detail.
received the B.E. and M.S. degrees in computer science from the Beijing University of Posts and Telecommunications (BUPT) in 1998 and 2001, respectively, and received Ph.D. degree in electrical engineering in 2004 from BUPT. From Aug. 2004 he joined DoCoMo Beijing Laboratories as an associate researcher, and was promoted to be a researcher in Dec. 2005. From Feb. 2006, he joined University of Alberta, Edmonton, AB, Canada, as a postdoctoral fellow. From Apr. 2009, he joined the Department of Research and Innovation (R&I), Alcatel-Lucent, Shanghai, as a Research Scientist. From Aug. 2010 to Jul. 2011, he worked in NEC China Laboratories, as a Senior Researcher. He is currently a professor of the School of Computer and Communication Engineering in the University of Science and Technology Beijing (USTB). His main research interests include statistical signal processing, self-organized networking, cognitive radio, and cooperative communications..