A pervasive optimized algorithm for complex network routing strategy

Abstract

There are many existing routing strategies in complex networks, but there is no uniform standard to measure whether the strategies achieve optimal transmission effect. A pervasive optimized algorithm is proposed. The key factor restricting transmission capacity is maximum betweenness centrality and minimizing it becomes the uniform standard. In order to make betweenness centrality more evenly distributed and balance the traffic load of each node, we use punishment selection method to avoid the nodes with larger betweenness centrality. The simulation results show that the new algorithm could reduce maximum betweenness centrality of existing strategies and improve the network transmittability greatly.

Routing Strategies for Isochronal-Evolution Random Matching Network

“…A routing strategy is defined as a routing decision-making algorithm using a certain path planning algorithm. In this paper, we focus on the shortest path routing strategy in the IERMN, not only because the shortest path routing strategy is the most popular in real-world networks [33], but also because of the characteristic topology of the IERMN.…”

“…There were differences in the routing strategy, the number of vertices Θ, and the delivery capability C among the eight scenarios. We set the values of C by referring to [33,36]. We performed simulations for each scenario with different packet generation rate R values in order to investigate the value of R C .…”