An effective edge-adding strategy for enhancing network traffic capacity

Abstract

With the rapid development of technology, the number of packets that need to be transmitted in the network is increasing, which leads to network congestion and reduces the user experience. Therefore, it is necessary to adjust the transmission path of packets in the network to improve the transmission threshold of packets in the network. In this paper, we abstract the real world network into a scale-free network for research, using nodes to represent individuals in reality, and edges to represent connections between individuals. Scale-free networks have serious inhomogeneity. Nodes in scale-free networks cannot be connected to all nodes in the network, which makes some gaps in the network. “Structural hole” describes the gaps in the network, which make some nodes have certain controllability to the whole network. But it only considers the relationship between nodes and their neighbors, without considering the overall structure of the whole network topology. K-shell decomposition algorithm can efficiently and accurately identify the location of nodes in the network. Therefore, K-shell decomposition algorithm is a global index. However, it still has shortcomings that does not consider the topological relationship between neighbors. Both structural hole and K-shell theory can characterize the importance of nodes. The combination of the two can make up for each other’s flaws and make the importance of nodes in the network more even. The more even the node importance, the more even the load of the node, the greater the increase in network traffic capacity. In this paper, we propose a network edge-adding strategy combining the structural hole theory and the k-shell algorithm to improve the traffic capacity. Extensive simulations have been performed to estimate the effectiveness of the proposed method under the efficient routing strategy. According to the simulation results, we can see that when the network size is fixed, regardless of the average degree of nodes, our proposed strategy improves the network traffic capacity, reduces the maximum betweenness centrality of nodes, and makes the load of nodes in the network more average. At the same time, our strategy improves the robustness of the network.