Designing principles and optimization approaches of a bio-inspired self-organized network

(Press-News.org) Contact information: YAN Bei
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Science China Press
Designing principles and optimization approaches of a bio-inspired self-organized network By observing the collective behaviors of social species, artificial self-organized systems are expected to exhibit some intelligent features that may have made social species so successful in the biosphere. However, it would never be easy to build an artificial self-organized network (SON) system as smart as a natural species. Professor ZHANG ZhongShan and his group from the Institute of Advanced Network Technology and New Services (ANTS), School of Computer and Communication Engineering (SCCE), University of Science and Technology Beijing (USTB), set out to address this problem. They surveyed different aspects of swarm intelligence and introduced various bio-inspired algorithms proposed to improve the performance of artificial SON systems. Their work, entitled "On the Designing Principles and Optimization Approaches of a Bio-Inspired Self-Organized Network: A Survey", was published in Science China Information Sciences 2013(7).

The challenges brought by the ever increasing complexity, heterogeneity, and dynamics in complex communications systems have inspired the studies on self-organization. However, there are no fundamental mechanisms and principles that have been generalized for designing artificial SON systems. Because the study of the collective behavior of social species can help us manage complex systems, bio-inspired algorithms will consequently enlighten us on designing, maintaining and optimizing artificial SON systems.

By studying the most essential and fundamental properties that are commonly observed in various natural species, four common mechanisms, including the Tendency to Re-Unite the Split sub-networks (TRUS), Consistency of the Task-Oriented Function (CTOF), Replaceable Roles (RR), and Cohesion-driven Tendency of Spontaneous Individual-homology and Group-harmony (C-TSIG), are investigated in the study. The four proposed fundamental mechanisms are critical to network planning and deployment and provide the fundamental principles for designing artificial systems from a macroscopic perspective. In addition, smart algorithms inspired by those less-fundamental attributes that are observed in some specific species can also be applied to optimizing the performance of artificial systems in terms of networking, operation, maintenance and optimization, etc., from a microscopic perspective.

In this paper, researchers discuss the networking and operational issues of artificial SON systems, applying some well-known bio-inspired algorithms to network synchronization, network scalability, distributed security, resource sharing and adaptive routing. Furthermore, several important issues regarding network maintenance and optimization, such as survival of the network, cooperation, load balancing and self-X capability are analyzed. Among the existing solutions, bio-inspired algorithms (e.g., ACO, BeeHive) have exhibited their capabilities in enabling artificial SON systems to be self-optimized, fault-tolerant and highly-scalable.

In addition, the properties of self-organization have already been exhibited in some technologies such as M2M communications and cellular mobile networks. Because the deployment and maintenance of cellular mobile networks are becoming progressively more complex and expensive with the rapid growth of mobile communications, more efficient strategies and smart algorithms have to be applied in future networks to further reduce CAPEX and OPEX. Much more attention has been paid to self-organization technologies to address these issues. The three main capabilities of self-organization, including self-configuration, self-optimization and self-healing, have been emphasized in 3GPP LTE systems, and with each of these technologies, several user cases with individual goals and requirements have been defined and standardized.

Although bio-inspired technologies have attracted increasing concern, their application to artificial SON systems is still a rather new research subject. Considering the ever increasing complexity, heterogeneity, and dynamics of communications networks, it will still be a challenging task in the future to propose more fundamental SON mechanisms and optimization algorithms that are universally applicable to variant heterogeneous networks.

### corresponding author： ZHANG ZhongShan
zhangzs@ustb.edu.cn

See the article: ZHANG ZhongShan, HUANGFU Wei, LONG KePing, ZHANG Xu, LIU XiaoYuan, ZHONG Bin. On the designing principles and optimization approaches of bio-inspired self-organized network: a survey. SCIENCE CHINA Information Sciences, 2013, 56(7): 071301(28)

http://info.scichina.com:8084/sciFe/EN/abstract/abstract511360.shtml

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