Influence of gross regional and industrial product ranks on data call connections.

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dc.contributor.authorKennedy, Ian Geoffrey
dc.date.accessioned2018-11-29T07:06:19Z
dc.date.available2018-11-29T07:06:19Z
dc.date.issued1992
dc.descriptionA thesis submitted to the Faculty of Engineering, University of the '\Vitwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophyen_ZA
dc.description.abstractTHIS STUDY identifies and evaluates factors that affect call connections in the South African public data networks, modelling these factors to aid data network planning. The research shows the relationship between the economic rank of each region served and the data communication resources required for that region. Moreover, it shows the resources required between regions. THE THRUST of this thesis is that the volume of cans from a region can be estimated from its economic ...k and more than 75% olthe variation in the volume of calls between regions can be explained using the ranks of the originating and terminating regions. To prove this, records of more than four million calls are accumulated for all regions of the South African packet switched data network. An appropriate filtering and aggregation method is developed. EXISTING growth models including the gravity model are separately examined. Based on probability and dimensional arguments, the Bell System growth model is selected. It is revealed that the success of this model depends on one premise being satisfied: this model tacitly anti implicitly assumes that the originating and terminating calls are statistically independent. RETURNING to the data network, it is found that the call connections (after filtering and aggregation) display dependence of destination on origin. Reasons for the dependence are discovered. Multiple linear regression reveals the nature of this dependence. Surprisingly, distance is not a factor. The importance of regional ranks and an inter-regional indicator variable are also discovered. FINALL Y, call volume from a node is shown to be directly linked with the weighted Gross Regional and Industrial Product of the region. This quantity, in tum, is inversely related to the rank of the region. Call connections are then modelled to be equal to the call connections within the first tanked region divided by the product of the originating region's rank and the terminating region's rank. This simple and economical model explains 76% of the variations that occur in call connections. It has proved its use by being included in the data transfer services product-line report.en_ZA
dc.description.librarianAndrew Chakane 2018en_ZA
dc.identifier.urihttps://hdl.handle.net/10539/26144
dc.language.isoenen_ZA
dc.subjectWide area networks (Computer networks) -- South Africa.en_ZA
dc.subjectTelecommunication -- South Africa.en_ZA
dc.subjectComputer networks -- South Africa.en_ZA
dc.titleInfluence of gross regional and industrial product ranks on data call connections.en_ZA
dc.typeThesisen_ZA
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