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

[摘要] THIS STUDY identifies and evaluates factors that affect call connections in the SouthAfrican public data networks, modelling these factors to aid data network planning. The researchshows the relationship between the economic rank of each region served and the datacommunication resources required for that region. Moreover, it shows the resources requiredbetween regions.THE THRUST of this thesis is that the volume of cans from a region can be estimatedfrom its economic ...k and more than 75% olthe variation in the volume of calls between regionscan be explained using the ranks of the originating and terminating regions. To prove this, recordsof more than four million calls are accumulated for all regions of the South African packetswitched data network. An appropriate filtering and aggregation method is developed.EXISTING growth models including the gravity model are separately examined. Basedon probability and dimensional arguments, the Bell System growth model is selected. It isrevealed that the success of this model depends on one premise being satisfied: this model tacitlyanti implicitly assumes that the originating and terminating calls are statistically independent.RETURNING to the data network, it is found that the call connections (after filteringand aggregation) display dependence of destination on origin. Reasons for the dependence arediscovered. 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 variableare also discovered.FINALL Y, call volume from a node is shown to be directly linked with the weightedGross Regional and Industrial Product of the region. This quantity, in tum, is inversely relatedto the rank of the region. Call connections are then modelled to be equal to the call connectionswithin the first tanked region divided by the product of the originating region's rank and theterminating region's rank. This simple and economical model explains 76% of the variations thatoccur in call connections. It has proved its use by being included in the data transfer servicesproduct-line report.

[发布机构] University of the Witwatersrand