On the designing principles and optimization approaches of bio-inspired self-organized network: a survey
On the designing principles and optimization approaches of bio-inspired self-organized network: a survey作者机构：Institute of Advanced Network Technology and New Services (ANTS) University of Science and Technology Beijing (USTB) Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing (USTB)
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2013年第56卷第7期
页 面：5-32页
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 081201[工学-计算机系统结构] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Basic Research Program of China (973 Program) (Grant No. 2012CB3159-05) National Natural Science Foundation of China (Grant No. 61172050) Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, National Key Projects (Grants Nos. 2012ZX03001029-005, 2012ZX03001032-003) Beijing Science and Technology Program (Grant No. Z1111000540- 11078) Program for New Century Excellent Talents in University (NECT-12-0774)
主 题：self-organized networking heterogeneous cognitive radio bio-inspired swarm intelligence decentralized load balancing cooperation
摘 要：A plethora of studies on self-organization has been carried out in broad areas including chemistry, biology, astronomy, medical science, telecommunications, etc., in both academia and industry. Following the studies on swarm intelligence observed in social species, the artificial self-organized systems are expected to exhibit some intelligent features (e.g., flexibility, robustness, decentralized control, self-evolution, etc.) that may have made social species so successful in the biosphere. In this paper, the application of swarm intelligence in communications networks will be studied, and we survey different aspects of bio-inspired mechanisms and examine various algorithms that have been proposed to improve the performance of artificial systems. Some fundamental self-organized networking (SON) mechanisms, designing principles and optimization approaches for artificial systems will then be investigated, followed by some well-known bio-inspired algorithms (e.g., cooperation, division of labor, distributed network synchronization, load balancing, etc.) as well as their applications to the maintenance/operation/optimization of artificial systems being analyzed. Besides, some new emerging technologies, such as the Self-X capabilities and cognitive machine-to-machine (M2M) optimization for the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE)/LTE-Advanced systems, are also surveyed. Finally, the remaining challenges to be faced in designing the future heterogeneous systems will be discussed.
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