Analysis of user density and quality of service using crowdsourced mobile network data

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dc.contributor.authorPanjwani, Nazma
dc.contributor.supervisorCoady, Yvonne
dc.contributor.supervisorNeville, Stephen William
dc.date.accessioned2021-09-07T20:27:12Z
dc.date.available2021-09-07T20:27:12Z
dc.date.copyright2021en_US
dc.date.issued2021-09-07
dc.degree.departmentDepartment of Computer Science
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractThis thesis analyzes the end-user quality of service (QoS) in cellular mobile networks using device-side measurements. Quality of service in a wireless network is a significant factor in determining a user's satisfaction. Customers' perception of poor QoS is one of the core sources of customer churn for telecommunications companies. A core focus of this work is on assessing how user density impacts QoS within cellular networks. Kernel density estimation is used to produce user density estimates for high, medium, and low density areas. The QoS distributions are then compared across these areas. The k-sample Anderson-Darling test is used to determine the degree to which user densities vary over time. In general, it is shown that users in higher density areas tend to experience overall lower QoS levels than those in lower density areas, even though these higher density areas service more subscribers. The conducted analyses highlight the value of mobile device-side QoS measurements in augmenting traditional network-side QoS measurements.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/13370
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectData Analysisen_US
dc.subjectBig Dataen_US
dc.subjectCrowdsourced dataen_US
dc.subjectMobile networken_US
dc.subjectKernel Density Estimationen_US
dc.subjectAnderson-Darlingen_US
dc.titleAnalysis of user density and quality of service using crowdsourced mobile network dataen_US
dc.typeThesisen_US

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