Mixed Routing Strategy Research Based On Scale-free Network With High Clustering

Since the 1990s, complex networks have developed into an independent research field. The existed different real systems in our living life can be regarded as complex networks. With the rapid development of communication network, the higher and higher demand of stability, timeliness and the effectiveness is needed by people. Thus, how to avoid network congestion has become the key to ensure the normal operation of the system. To solve the problem, it's need to find the right network model, and the routing strategy. So, the main work of this paper contains the following parts.First, based on scale free network,it has proposed two improved network models which degree distribution and clustering coefficient can be adjusted. The two models jointly considering "triangle structure", "internal evolution" “community structure”. Considering a single node and community respectively when a new node joins in network. The mechanism of triangle moved to old nodes in the evolution of network.Then, based on the improved models, a mixed routing strategy integrating static and dynamic information is proposed. Betweenness is assumed to be node's delivering ability. With the combination of shortest path algorithm and optimized transmission, the capacity of network achieve the maximum by adjusting parameter.Simulations show that compared to traditional network models are only scaling or high clustering, the two improved models follow the high clustering and scale free properties.Power index and clustering coefficient can be adapted to different networks by adjusting parameters, clustering coefficient can be as high as 0.5, the models are closer to real networks. The improved routing strategy is applied to two improved models. Capacity of the network can reach 300 and 350 respectively, critical capacity of network is usually less than 100. Maximum of the network capacity has improved compared to other mixed routing strategies in the same condition.