An adjacency matrix approach to delay analysis in temporal networks
An adjacency matrix approach to delay analysis in temporal networks
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DOI：
10.1109/milcom.2017.8170866
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
J. Shea;J. Macker
中科院分区：
文献类型：
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作者：
J. Shea;J. Macker
无线通信网络通常被建模为图，其中顶点表示无线设备，而边表示它们之间的通信链路。然而，图形无法捕捉无线网络的时变特性。时间网络是其中节点或边的集合是时变的图。我们考虑最常见的情况下，其中节点的集合是固定的，但边的存在随着时间的推移而变化。大多数以前的工作都集中在分析时间网络的总结措施，联合收割机的贡献，不同的路径使用不同的权重不同的延迟。这样的汇总测量对于计算是有效的，但是可能丢失关于网络的时间行为的有价值的信息。我们提出的技术，其特征的时间网络中的节点之间的所有路径的延迟。然后，我们应用这些技术来识别连接节点的时间路径中的主导模式。示例时间网络被用来说明这些现象，我们认为无线网络的影响。
Wireless communications networks are often modeled as graphs in which the vertices represent wireless devices and the edges represent the communication links between them. However, graphs fail to capture the time-varying nature of wireless networks. Temporal networks are graphs in which the sets of nodes or edges are time-varying. We consider the most common case, in which the set of nodes is fixed but the presence of edges changes over time. Most previous work on analyzing temporal networks has focused on summary measures that combine the contributions of different paths by using different weights for paths with different delays. Such summary measures are efficient to compute but may lose valuable information about the temporal behavior of the network. We propose techniques that characterize the delays of all paths between nodes in temporal networks. We then apply these techniques to identify dominant patterns in the temporal paths connecting nodes. Example temporal networks are used to illustrate these phenomena, and we consider implications to wireless networks.