Coverage and hole-detection in sensor networks via homology
Coverage and hole-detection in sensor networks via homology
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DOI：
10.1109/ipsn.2005.1440933
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发表时间：
2005-04
期刊：
影响因子：
--
通讯作者：
R. Ghrist;Abubakr Muhammad
中科院分区：
文献类型：
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作者：
R. Ghrist;Abubakr Muhammad
我们考虑传感器网络中的覆盖问题的固定节点的最小几何数据。特别是，没有坐标，也没有节点的定位。我们介绍了一种新的技术，用于检测覆盖的同源性，代数拓扑不变量的漏洞。这些技术的推动力是完成网络通信图到两种类型的单纯复合体：神经复合体和裂口复合体。前者给出了单个传感器节点的覆盖交集信息，计算非常困难。后者捕获节点间通信的连通性：它很容易计算，但本身并不产生覆盖数据。我们获得覆盖数据，通过使用持久性的同源类的RIP复合物。这些同调不变量是可计算的：我们提供模拟结果。
We consider coverage problems in sensor networks of stationary nodes with minimal geometric data. In particular, there are no coordinates and no localization of nodes. We introduce a new technique for detecting holes in coverage by means of homology, an algebraic topological invariant. The impetus for these techniques is a completion of network communication graphs to two types of simplicial complexes: the nerve complex and the Rips complex. The former gives information about coverage intersection of individual sensor nodes, and is very difficult to compute. The latter captures connectivity in terms of inter-node communication: it is easy to compute but does not in itself yield coverage data. We obtain coverage data by using persistence of homology classes for Rips complexes. These homological invariants are computable: we provide simulation results.