An effective probabilistic routing strategy based on gravitational centrality in complex networks

Abstract

Preventing packet congestion in communication networks is a critical challenge. A conventional routing strategy based on node degree to prevent congestion has demonstrated good performance in improving the traffic capacity within communication networks. However, this approach fails to differentiate between nodes with the same degree. Furthermore, since multiple nodes with the same degree exist in complex networks, the evaluation of importance based on node degree has its limitations. Addressing this limitation, we propose a probabilistic routing strategy that utilizes gravitational centrality. Our proposed strategy, however, differentiates the importance of nodes by employing a probabilistic function based on gravitational centrality rather than node degree, thereby allowing nodes with identical degrees to have varying levels of importance. Numerical experiments demonstrated that the proposed strategy achieves more than 19% larger traffic capacity compared to the efficient routing strategy, more than 13.4% larger traffic capacity compared to the effective gravitation path routing strategy, and over 16% larger traffic capacity compared to the probability routing strategy.