The Relationship Of Network Topology And Search Strategy On Complex Network

The rapid development of information technology makes computer network become a large-scale complex network while the complex systems in the real world can be represented via the complex networks. Thus, to model a complex network and to study of the complex network’s dynamic behaviors becomes a significantly important research issue. The complex network dynamics is closely related with the network topology, and this paper intends to work on how the network topology affects the network information search. The topology structure’s influence on the information search can be manifested in two ways:the network search performance (i.e. the shortest average path), network search algorithm. Hence, this paper attempts to study the network topological features’influences on the information search from the two levels.Firstly, we establish the BA scale-free model and change its assortativity coefficient, and then, discuss the assortativity coefficient’s impacts on network search. Through the simulation experiment, we found out that the disassortative scale-free network and the low assortative network share the a shorter average path which is suitable for information search; while the high assortative network’s average path is relatively longer which is unsuitable for information search. The maximum-scale search algorithm is suitable for the disassortative scale-free network and the low assortative network, not for the high assortative network. In the high assortative network, the shortest scale search algorithm is even worse than the random search algorithm.Then, under the scale free network and the small world network, we study the clustering coefficient’s impacts on the network search. Through the simulation experiment, we found out that the shortest average path in the scale free network decreases with the increase of the clustering coefficient and the shortest average path in the small world network increases with the increase of the clustering coefficient, which illustrates that clustering features contribute to the information search in the scale free network, while in the small world network, over clustering features go against the information search.