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February 27, 20260 citationsOpen Access

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

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KOKisembo OlelaNMNdirangu MugoMNMwangi Ngina

Key Points

  • The central research aim is to enhance telecom network reliability in Kenya using Topological Data Analysis and simulation techniques.
  • Developed a theoretical model based on network topology and user behaviour assumptions.
  • Incorporated Topological Data Analysis and Monte Carlo simulations for reliability estimation.
  • Analyzed network performance variability using advanced statistical techniques.
  • Substantial improvements in predicting telecom network performance variability were observed.
  • The theoretical framework provides a robust method for assessing network reliability.

Abstract

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 yₜ=F (xₜ;) with =argmin_L (), and convergence is established under standard smoothness conditions.

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Cite This Study

Olela et al. (2003) studied this question.

synapsesocial.com/papers/69a1353eed1d949a99abefcfhttps://doi.org/10.5281/zenodo.18768366
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