Modeling downtime severity of telecommunication networks using discrete time markov Chains

Abstract

Telecommunication network reliability has remained a top priority among both customers and telecommunication service providers (SPs). Telecommunication network downtime can lead to a loss of revenue for the SPs and a loss in productivity for the customer. Hence, having a model that can accurately predict the downtime severity of telecommunication networks will go a long way to help SPs plan early and be ready to deal with downtime when it occurs. In this study, we model the downtime severity of telecommunication networks using discrete-time Markov chains (DTMC). The data used in this empirical study consist of 1,211 total daily network downtime, in minutes, recorded by the national communications authority (NCA) in Ghana, spanning the period August 01, 2015, to April 30, 2021. The severity of the daily downtime data was categorized into 5 categories, depending on the duration of the downtime. The results indicate that the majority (n=905) of the daily network downtime recorded was negligible while only 25 of the outages were severe. The transition probability matrix revealed that when the present network downtime severity is negligible, then there is an 81% chance that the next network downtime severity will still be negligible, a 12% chance that the next network downtime severity will be minimal, a 4% chance that the next network downtime severity will be significant, 2% chance that the next network downtime severity will be serious, and 1% chance that the next network downtime will be severe. The steady-state distribution indicates that in the long run (n ? 17), 74% of the network downtime severity will be negligible while only 2% of the network downtime will be severe. We also checked and simulated the probabilities of a network downtime severity for 12 steps. It seemed apparent that the most likely network downtime severity category is �negligible�, irrespective of the initial severity category. These findings will help telecommunication SPs plan better to provide more reliable services to their customers. � The Authors.