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Topological Data Analysis Underpinning Telecom Network Reliability in Kenya: Monte Carlo Estimation with Variance Reduction

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Bibliographic Details
Main Authors:	Olela, Kisembo, Mugo, Ndirangu, Ngina, Mwangi, Kimaro, Otombe
Format:	Recurso digital
Language:	English
Published:	Zenodo 2003
Subjects:	Kenyan Topology Persistence Diagrams Simplicial Complexes Monte Carlo Variance Reduction Cohomology
Online Access:	Acceder al recurso
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_version_	1866901068032507904
author	Olela, Kisembo Mugo, Ndirangu Ngina, Mwangi Kimaro, Otombe
author_facet	Olela, Kisembo Mugo, Ndirangu Ngina, Mwangi Kimaro, Otombe
contents	<p>This study explores how Topological Data Analysis (TDA) can be applied to improve the reliability of telecom networks in Kenya. A theoretical model will be developed based on assumptions regarding network topology and user behaviour. The methodology will incorporate principles from TDA and Monte Carlo simulations for estimating reliability metrics under varying conditions. This theoretical framework provides a robust method for assessing telecom network reliability using TDA and advanced statistical techniques. The findings suggest substantial improvements in predicting network performance variability. Future research should validate these theoretical results through empirical testing on real-world network data, with the aim of enhancing network design and maintenance strategies. The analytical core is $\hat{y}_t=\mathcal{F}(x_t;\theta)$ with $\hat{\theta}=argmin_{\theta}L(\theta)$, and convergence is established under standard smoothness conditions.</p>
format	Recurso digital
id	zenodo_https___doi_org_10_5281_zenodo_18768367
institution	Zenodo
language	eng
publishDate	2003
publisher	Zenodo
record_format	zenodo
spellingShingle	Topological Data Analysis Underpinning Telecom Network Reliability in Kenya: Monte Carlo Estimation with Variance Reduction Olela, Kisembo Mugo, Ndirangu Ngina, Mwangi Kimaro, Otombe Kenyan Topology Persistence Diagrams Simplicial Complexes Monte Carlo Variance Reduction Cohomology <p>This study explores how Topological Data Analysis (TDA) can be applied to improve the reliability of telecom networks in Kenya. A theoretical model will be developed based on assumptions regarding network topology and user behaviour. The methodology will incorporate principles from TDA and Monte Carlo simulations for estimating reliability metrics under varying conditions. This theoretical framework provides a robust method for assessing telecom network reliability using TDA and advanced statistical techniques. The findings suggest substantial improvements in predicting network performance variability. Future research should validate these theoretical results through empirical testing on real-world network data, with the aim of enhancing network design and maintenance strategies. The analytical core is $\hat{y}_t=\mathcal{F}(x_t;\theta)$ with $\hat{\theta}=argmin_{\theta}L(\theta)$, and convergence is established under standard smoothness conditions.</p>
title	Topological Data Analysis Underpinning Telecom Network Reliability in Kenya: Monte Carlo Estimation with Variance Reduction
topic	Kenyan Topology Persistence Diagrams Simplicial Complexes Monte Carlo Variance Reduction Cohomology
url	https://doi.org/10.5281/zenodo.18768367