A Time-Ordered Aggregation Model-Based Centrality Metric for Mobile Social Networks

Huan Zhou, Mengni Ruan, Chunsheng Zhu, Victor C.M. Leung, Shouzhi Xu, Chung Ming Huang

研究成果: Article同行評審

31 引文 斯高帕斯(Scopus)

摘要

How to measure the centrality of nodes is a significant problem in mobile social networks (MSNs). Current studies in MSNs mainly focus on measuring the centrality of nodes in a certain time interval based on the static graph that do not change over time. However, the network topology of MSNs is changing very rapidly, which is the main characteristic of MSNs. Therefore, it will not be accurate to measure the centrality of nodes in a certain time interval by using the static graph. To solve this problem, this paper first introduces a new centrality metric named cumulative neighboring relationship (CNR) for MSNs. Then, a time-ordered aggregation model is proposed to reduce a dynamic network to a series of time-ordered networks. Based on the time-ordered aggregation model, this paper proposes three particular time-ordered aggregation methods and combines with the proposed centrality metric CNR to measure the importance of nodes in a certain time interval. Finally, extensive trace-driven simulations are conducted to evaluate the performance of our proposed time-ordered aggregation model-based centrality metric time-ordered cumulative neighboring relationship (TCNR). The results show that the exponential time-ordered aggregation method can measure TCNR centrality in a certain time interval more accurately than other aggregation methods, and our proposed time-ordered aggregation model-based centrality metric TCNR outperforms other existing temporal centrality metrics.

原文English
頁(從 - 到)25588-25599
頁數12
期刊IEEE Access
6
DOIs
出版狀態Published - 2018 四月 27

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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