Abstract Persistent Betti numbers are a major tool in persistent homology, a subfield of topological data analysis. Many tools in persistent homology rely on the properties of persistent Betti numbers considered as a two-dimensional stochastic process$$ (r,s) \mapsto n^{-1/2} (\beta^{r,s}_q ( \mathcal{K}(n^{1/d} \mathcal{X}_n))-\mathbb{E}[\beta^{r,s}_q ( \mathcal{K}( n^{1/d} \mathcal{X}_n))])$$. So far, pointwise limit theorems have been established in various settings. In particular, the pointwise asymptotic normality of (persistent) Betti numbers has been established for stationary Poisson processes and binomial processes with constant intensity function in the so-called critical (or thermodynamic) regime; see Yogeshwaranet al.(Prob. Theory Relat. Fields167, 2017) and Hiraokaet al.(Ann. Appl. Prob.28, 2018). In this contribution, we derive a strong stabilization property (in the spirit of Penrose and Yukich,Ann. Appl. Prob.11, 2001) of persistent Betti numbers, and we generalize the existing results on their asymptotic normality to the multivariate case and to a broader class of underlying Poisson and binomial processes. Most importantly, we show that multivariate asymptotic normality holds for all pairs (r,s),$$0\le r\le s<\infty$$, and that it is not affected by percolation effects in the underlying random geometric graph.
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On the Range Assignment in Wireless Sensor Networks for Minimizing the Coverage-Connectivity Cost
This article deals with reliable and unreliable mobile sensors having identical sensing radiusr, communication radiusR, provided thatr≤Rand initially randomly deployedon the planeby dropping them from an aircraft according to general random process. The sensors have to move from their initial random positions to the final destinations to provide greedy pathk1-coverage simultaneously withk2-connectivity. In particular, we are interested in assigning the sensing radiusrand communication radiusRto minimizethe time requiredandthe energy consumptionof transportation cost for sensors to provide the desiredk1-coverage withk2-connectivity. We prove that for both of these optimization problems, the optimal solution is to assign the sensing radius equal tor=k1||E[S]||/2 and the communication radiusR=k2||E[S]||/2, where ||E[S]|| is the characteristic of general random process according to which the sensors are deployed. Whenr<k1||E[S]||/2 orR<k2||E[S]||/ 2, and sensors are reliable, we discover and explainthe sharp increasein the time required and the energy consumption in transportation cost to ensure the desiredk1-coverage withk2-connectivity.
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- Award ID(s):
- 2104078
- PAR ID:
- 10634007
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM Transactions on Sensor Networks
- Volume:
- 17
- Issue:
- 4
- ISSN:
- 1550-4859
- Page Range / eLocation ID:
- 1 to 48
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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