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dc.contributor.advisorKilmartin, Liam
dc.contributor.authorWang, Han
dc.description.abstractThis thesis describes work completed on the characterisation and modelling of the behaviour of subscribers in mobile phone networks implementing dynamic pricing by means of Call Detail Records (CDR) datasets analysis. The initial focus of the work was the development of algorithms and visualisation techniques to facilitate an investigation of general subscriber behaviour in the Ugandan mobile phone network in which the CDR datasets was recorded. A cell site location estimation algorithm was developed which provided initial estimates for the location of cell sites which in 80% of all cell sites was within 20km of their true location. A joint calling and mobility analysis showed that the majority of subscribers visited fewer than six cells and that these subscribers usually made fewer than six calls per day. A coarse-graining strategy was also applied to identify the most significant communications corridors between the major urban centres in the country. The second component of this work was an investigation into what insights the CDR datasets could provide relating to aspects of social behaviour and economic activity in Uganda. A methodology for identifying centres of population concentration for residential and work activities was developed. This analysis highlighted a pattern where economic activity appeared to be concentrated around a small number of urban centres. Significant regional insularity in terms of population movement and communication was also observed along with regional behavioural homogeneity, particularly in the populations of Eastern and Western regions of the country compared to behaviour in the region around the capital and in the economically under-developed Northern region. The final component of this work focussed on the development of a novel Agent Based Model (ABM) for the simulation of subscriber behaviour based on patterns observed in the CDR datasets. Results showed that the simulated behaviour observed in the ABM bore strong similarities to that observed in the CDR datasets. The ABM was then utilised as a tool to evaluate the likely levels of revenue generation for a number of different dynamic pricing algorithms. Results obtained using the ABM suggested that all the dynamic pricing regimes investigated would likely result in revenue losses between 6% and 30% with a fixed subscriber base). Additional results also indicated that the scope for using optimisation techniques for revenue maximisation through real time control of dynamic pricing algorithms may be limited.en_IE
dc.publisherNUI Galway
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.subjectDynamic pricingen_IE
dc.subjectAgent-based modelen_IE
dc.subjectRevenue optimisationen_IE
dc.subjectMobile network servicesen_IE
dc.subjectCDR dataen_IE
dc.subjectBig dataen_IE
dc.subjectGraph theoryen_IE
dc.subjectEngineering and Informaticsen_IE
dc.subjectElectrical and Electronic Engineeringen_IE
dc.titleOn the application of analytical techniques to mobile network CDRs for the characterisation and modelling of subscriber behaviouren_IE
dc.contributor.funderIrish Research Council for Science, Engineering and Technologyen_IE
dc.contributor.funderTango Telecomen_IE
dc.local.noteThe work in this research is on the application for data analytics and modelling techniques to the behaviour of subscribers of mobile telephony networks. The work was based on a huge dataset of several million Call Detail Records (CDRs) generated in a mobile network in the country of Uganda which was implementing a dynamic pricing service where the tariff charged to subscribers for voice calls varied dynamically based on the location of the subscriber and the time of day. The research reported in the thesis comprises of three distinct parts. The first part outlines various data analysis, statistical modelling and visualisation techniques which were applied to the dataset in order to gain insights into the high level behaviour of subscribers in this network. This included investigations into subscribers’ calling behaviour, their mobility and their uptake of the voice service and how this varied with the tariff discount offered to them. The second part of the work focussed on utilising the CDR data set as a means of gaining insights into some aspects of social and economic life in Uganda. Of particular interest was an attempt to understand whether such data sets can genuinely be used as surrogates for census, surveys and other more traditional techniques as a basis for investigation relating to socio-economic behaviour. The final part of the thesis focusses on the development of a novel modelling tool, using an approach called Agent Based Modelling (ABM), which allows the user to simulate mobile network operator revenue generation for dynamically priced voice services. The overall model utilises statistical model relating to subscriber behaviour (e.g. calling and mobility behaviour) determined in the earlier work examining the real behaviour of subscribers in the Ugandan network. The developed model was then used to investigate the revenue generation capabilities of a number of different dynamic pricing algorithms which could be deployed and compared these to the cell site load based dynamic pricing algorithm which was actually deployed in the real Ugandan network.en_IE

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