Title :
Robustness during Network Evolution
Author :
He, Chunquan ; Ren, Qingsheng
Author_Institution :
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai
Abstract :
Robust networks can maintain their characteristics under perturbation, which is rooted in the different topology structure.However, previous study of the relationship between network robustness and topology structure is based on a static context. We study the effects of network topology on the network robustness from an dynamic points of view. We explore robustness to two types of perturbation on two categories of networks during network evolution to perform some pre-established function. We demonstrated that scale-free networks perform inferior to homogenous random graph on mutational robustness, which facilitates the evolutionary search to perform the target function; while they are superior on robustness of attractors to random graph, which demonstrates the higher tolerance to state inversion. These results may highlight the ubiquitous existence of scale-free topologies in nature.
Keywords :
evolutionary computation; graph theory; network topology; evolutionary search; homogenous random graph; mutational robustness; network evolution; network robustness; network topology; perturbation; robust networks; scale-free networks; scale-free topologies; state inversion; static context; target function; topology structure; Biological system modeling; Boolean functions; Competitive intelligence; Evolution (biology); Evolutionary computation; Intelligent networks; Intelligent structures; Network topology; Noise robustness; Software maintenance; Attractor; Boolean Network; Evolutionary Algorithm; Mutational Robustness; Network Evolution; Network Robustness;
Conference_Titel :
Complex, Intelligent and Software Intensive Systems, 2009. CISIS '09. International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4244-3569-2
Electronic_ISBN :
978-0-7695-3575-3
DOI :
10.1109/CISIS.2009.135