In this thesis we investigate the performance of spatial reuse in wireless networks. More specifically, we investigate the performance of location-based spatial reuse built upon the identification of links in the network that form Collision-Free Sets (CFSs). We develop algorithms that efficiently find such CFSs. The main focus of this thesis is the application of our CFS-based algorithms to emerging WiMAX (Worldwide Interoperability for Microwave Access) networks. However, we will also apply our CFS-based algorithms to smaller scale networks, as well as to the issue of QoS routing. This thesis makes several contributions. We first show how CFSs can be found within polynomial time in small scale wireless networks. We then probe how CFSs can be used to enhance network efficiency when location is available. We also explore how CFS determination is affected by location error, determining what level of location error renders the use of CFSs ineffective. In this context, we discuss the density of access points required to ensure CFS-based spatial reuse remains effective. We then focus on the use of CFSs in emerging multihop WiMAX networks, showing in detail how enhanced spatial reuse is delivered. The spatial reuse gains are probed both in the presence of realistic channel conditions and realistic location errors. Within the context of the IEEE 802.16 standard we show how CFSs can enhance, by factors of two, the VoIP capacity of multihop WiMAX networks. We also discuss how our CFS algorithms can be applied to other ongoing efforts aimed at improving VoIP capacity in WiMAX networks. Finally, an application of our CFS algorithms in the context of QoS routing is studied. Specifically, we develop a two-hop QoS routing protocol that guarantees QoS specifications by securing higher bandwidth for the chosen routes.

Errors are inherent to all spatial datasets and give rise to a level of uncertainty in the final product of a geographic information system (GIS). There is growing recognition that the uncertainty associated with spatial information should be represented to users in a comprehensive and unambiguous way. However, the effects on decision-making of such representations have not been thoroughly investigated. Studies from the psychological literature indicate decision-making biases when information is uncertain. This study explores the effects of representing spatial uncertainty, through an examination of how decision-making may be affected by the introduction of thematic uncertainty and an investigation of the effects of different representations of positional uncertainty on decision-making. / Two case studies are presented. The first of these considers the effects on decision-making of including thematic uncertainty information within the context of an airport siting decision task. An extremely significant tendency to select a zone for which the thematic classification is known to be of high certainty was observed. The reluctance to select a zone for which the thematic classification is of low certainty was strong enough to sometimes lead to decision-making that can only be described as irrational. / The second case study investigates how decision-making may be affected by different representations of positional uncertainty within the context of maritime navigation. The same uncertainty information was presented to participants using four different display methods. Significant differences in their decisions were observed. Strong preferences for certain display methods were also exhibited, with some representations being ranked significantly higher than others. / The findings from these preliminary studies demonstrate that the inclusion of uncertainty information does influence decision-making but does not necessarily lead to better decisions. A bias against information of low certainty was observed, sometimes leading to the making of irrational decisions. In addition, the form of uncertainty representation itself may affect decision-making. Further research into the effects on decision-making of representing spatial uncertainty is needed before it can be assumed that the inclusion of such information will lead to more informed decisions being made.

Thesis (M.App.Sc.)(GIS)--University of Melbourne, Dept. of Geomatics, 2005. / Typescript (photocopy). Includes bibliographical references (leaves 134-148).

Thesis (Ph.D.)--University of Melbourne, Dept. of Geomatics, Faculty of Engineering, 2006. / Author's name on spine: K. McDougall. Spine title: Local-State government SDI partnership model. Includes bibliographical references (p. 233-251).

Thesis (Ph.D.) -- University of Melbourne, Dept. of Geomatics, 2005. / Typescript. Includes bibliographical references (p. 233-248).

Thesis (M.S.)--Ohio University, March, 1998. / Title from PDF t.p.

Dissertation (Ph.D.)--Auburn University, 2005. / Abstract. Vita. Includes bibliographic references (p.144-149).

Thesis (Ph. D.)--University of Hong Kong, 1992.

Thesis (M.Sc.(Geoinformatics))--University of Pretoria, 2001. / Summary in English. Includes bibliographical references.

Please read the abstract in the section 00front of this document / Dissertation (MSc)--University of Pretoria, 2001. / Geography, Geoinformatics and Meteorology / MSc / Unrestricted