Modeling networks as different graph types and researching on route finding strategies, to avoid congestion in dense subnetworks via graph-theoretic approaches, contributes to overall blocking probability reduction in networks. Our main focus is to study methods for modeling congested subnetworks and graph density measures, in order to identify routes that avoid dense subgraphs for global congestion avoidance, along with covering related algorithmic issues.
翻译:以不同的图表类型建模网络和研究路线搜索战略,以避免通过图形理论方法造成密集子网络的拥堵,这有助于全面阻断网络的概率降低,我们的主要重点是研究模拟凝聚子网络的方法和图形密度测量,以便确定避免全球拥堵的密集子集线,同时涵盖相关的算法问题。