基于拓扑凝聚图的机会网络关键节点评估

评估机会网络的关键节点可以发现对网络吞吐量影响最大的节点，为网络的优化和维护提供支撑.为此，针对机会网络拓扑结构动态变化的特性构建了拓扑凝聚图，定义了二阶节点度、连接强度和关键域重要度3个评估指标，以指标的欧式距离表征节点的重要性.实验结果表明，与介数中心性方法相比，提出的模型具有有效性和优越性，并且模型在时间窗取20 min时具有较高的精度.

Critical Nodes Evaluation of Opportunistic Networks Based on Topological Condensation Graph

By evaluating critical nodes of opportunistic networks, it was found the nodes that have the greatest influence on the throughput of network, which can support for network optimization and maintenance. The topological condensation graph was constructed according to the characteristics of frequent topology changes in opportunistic networks, and three evaluation metrics, such as second-order degree, connection strength, and key domain importance, were defined. The Euclidean distance of the metrics was employed to characterize the importance of the nodes. Experiments show that the proposed model is effective and superior compared with the betweenness method, and the model has higher accuracy when the time window is set for 20 minutes.