Abstract
In wireless networks, the betweenness of a node has been considered an indication of that node’s importance in efficiently and reliably delivering messages. In a large wireless network, however, the cost of computing the betweenness of every node is impractically high. In this paper, we introduce a new representation of a node’s vicinity, called the expanded ego network (shortly, x-ego network) of that node. We also propose an approach that calculates the x-ego betweenness of a node (i.e., the betweenness of that node in its x-ego network) and use it as an estimate of the true betweenness in the entire network. Furthermore, we develop an algorithm that quickly computes x-ego betweenness by exploiting structural properties of x-ego networks. Our evaluation results show the benefits and effectiveness of the above approach using trace data obtained from real-world wireless networks.
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Notes
We use the term node and social link to refer to the devices and their relationships in a wireless network. On the other hand, the graph representing a wireless network consists of vertices and edges representing nodes and social links, respectively.
In \(\mathcal {X}_{{v}}\), all vertices including n are at most 2 hops away from v. n≠v cannot be a 2-hop neighbor of v since it is a 1-hop neighbor of t, which is a 2-hop neighbor of v. Therefore, n can only be a 1-hop neighbor of v.
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Acknowledgements
This work has been supported by the National Science Foundation under CAREER award IIS-1149372, and also supported by Basic Science Research Program through the National Research Foundation (NRF) of Korea (No. NRF-2013R1A1A2010050).
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Kim, CM., Kim, Yh., Han, YH. et al. Efficient Estimation of Betweenness Centrality in Wireless Networks. Mobile Netw Appl 21, 469–481 (2016). https://doi.org/10.1007/s11036-015-0660-x
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DOI: https://doi.org/10.1007/s11036-015-0660-x