KayusQoS: A Mobile-Driven Software Framework for Real-Time QoS Data Collection and Knowledge Discovery in Nigerian GSM Networks

Abstract

The Nigerian telecommunications industry relies largely on expensive and manually intensive drive-test systems for monitoring Quality of Service (QoS), which limits the frequency, coverage and affordability of performance assessment, particularly in semi-urban environments. This study presents KayusQoS, a mobile-driven software framework for automated QoS data collection and knowledge discovery in Global System for Mobile Communications (GSM) networks. The framework integrates an Android-based application for real-time capture of Key Performance Indicators (KPIs) and a Knowledge Discovery in Databases (KDD) analytical process for data preprocessing, analysis and interpretation. The study adopted a hybrid research design combining system development and experimental validation. Using the KayusQoS application, a total of 2,944 valid call records were collected from four major GSM operators, namely MTN, Airtel, GLO and 9Mobile, across selected Local Government Areas of Nasarawa State, Nigeria. Five Key Performance Indicators—Call Setup Success Rate, Call Drop Rate, Handover Success Rate, Received Signal Strength and Retainability Rate—were computed and benchmarked against Nigerian Communications Commission Quality of Service thresholds. Results indicate that the KayusQoS framework achieved full automation and 100 percent geo-tagging accuracy. MTN demonstrated the highest overall Quality of Service performance, while Airtel showed moderate compliance with regulatory benchmarks. GLO and 9Mobile exhibited lower performance levels in several indicators. The study concludes that KayusQoS is a reliable, low-cost and effective alternative to conventional drive-test systems and can serve as a complementary tool for regulatory monitoring and network optimization in Nigeria.