Gao Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 70-73). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Survey and Background --- p.6 / Chapter 2.1 --- Capacity of Wireless Networks --- p.6 / Chapter 2.2 --- Physical Layer Techniques --- p.8 / Chapter 2.2.1 --- Radio Propagation Models --- p.8 / Chapter 2.2.2 --- Multiple Access Techniques --- p.11 / Chapter 2.3 --- MAC layer --- p.13 / Chapter 2.3.1 --- An Introduction to the IEEE 802.11 protocol --- p.13 / Chapter 2.3.2 --- Performance Analysis of the IEEE 802.11 protocol in single cell networks --- p.15 / Chapter 3 --- Model and Methodology --- p.18 / Chapter 3.1 --- System Model --- p.18 / Chapter 3.1.1 --- DCF Model --- p.19 / Chapter 3.1.2 --- The Problems of Hidden Node --- p.21 / Chapter 3.2 --- A Methodology to Compute Throughput Capacity --- p.23 / Chapter 3.2.1 --- Constructing a Contention Graph --- p.24 / Chapter 3.2.2 --- Determining the Link Capacity Ei --- p.27 / Chapter 3.2.3 --- Determining the Channel Idle Probability zi --- p.30 / Chapter 3.2.4 --- Detennining the Collision Probability γi --- p.32 / Chapter 3.3 --- Throughput Analysis of a Chain network --- p.35 / Chapter 4 --- Applications of the Proposed Methodology --- p.38 / Chapter 4.1 --- Application 1: Determining the End-to-End Throughput Capacity in Multi-hop Networks --- p.38 / Chapter 4.1.1 --- Routing Optimization --- p.40 / Chapter 4.1.2 --- Offered Load Control --- p.45 / Chapter 4.2 --- Application 2: Determining the Equilibrium Throughput of onehop Networks --- p.47 / Chapter 4.2.1 --- Throughput Capacity of One-Hop Networks --- p.49 / Chapter 4.3 --- Application 3: Optimal Hop Distance in Multi-hop Networks --- p.51 / Chapter 4.3.1 --- Analysis of Regular One-Dimension Network --- p.51 / Chapter 4.3.2 --- Optimal Hop Distance --- p.53 / Chapter 5 --- Simulation and Validation --- p.55 / Chapter 5.1 --- Simulation Environment --- p.55 / Chapter 5.2 --- MAC layer Collisions --- p.56 / Chapter 5.3 --- Single Flow Capacity: --- p.58 / Chapter 5.4 --- Neighboring Traffic Effect: --- p.59 / Chapter 5.5 --- Routing Optimization: --- p.60 / Chapter 5.6 --- Optimal Offered Load Control: --- p.62 / Chapter 5.7 --- Optimal Hop Distance --- p.63 / Chapter 5.7.1 --- One-Source ROD Network --- p.63 / Chapter 5.7.2 --- Two-Source ROD Network --- p.64 / Chapter 5.7.3 --- Simulation Investigation on Hop Distance --- p.65 / Chapter 6 --- Related Work --- p.68 / Chapter 7 --- Conclusion --- p.69

Zheng, Pengxuan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 53-57). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.v / Table of Contents --- p.vi / List of Figures --- p.viii / List of Tables --- p.ix / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Related Work --- p.2 / Chapter 1.3 --- Our Contribution --- p.3 / Chapter 1.4 --- Organization of the Thesis --- p.4 / Chapter Chapter 2 --- Background Overview --- p.6 / Chapter 2.1.1 --- Traditional Wireless Networks --- p.6 / Chapter 2.2 --- Exponential Backoff --- p.7 / Chapter 2.2.1 --- Introduction --- p.7 / Chapter 2.2.2 --- Algorithm --- p.8 / Chapter 2.2.3 --- Assumptions --- p.9 / Chapter 2.3 --- System Description --- p.9 / Chapter 2.3.1 --- MPR Capability --- p.9 / Chapter 2.3.2 --- Backoff Slot --- p.10 / Chapter 2.3.3 --- Carrier-sensing and Non-carrier-sensing Systems --- p.11 / Chapter Chapter 3 --- Multipacket Reception in WLAN --- p.12 / Chapter 3.1 --- MAC Protocol Description --- p.13 / Chapter 3.2 --- Physical Layer Methodology --- p.16 / Chapter 3.2.1 --- Blind RTS Separation --- p.17 / Chapter 3.2.2 --- Data Packet Detection --- p.19 / Chapter Chapter 4 --- Exponential Backoff with MPR --- p.21 / Chapter 4.1 --- Analytical Model --- p.22 / Chapter 4.1.1 --- Markov Model --- p.22 / Chapter 4.1.2 --- Relations betweenpt andpc --- p.23 / Chapter 4.2 --- Simulation Settings --- p.26 / Chapter 4.3 --- Asymptotic Behavior of Exponential Backoff --- p.27 / Chapter 4.3.1 --- Convergence ofpt andpc --- p.27 / Chapter 4.3.2 --- Convergence of Npt --- p.29 / Chapter Chapter 5 --- Non-carrier-sensing System --- p.31 / Chapter 5.1 --- Performance Analysis --- p.31 / Chapter 5.1.1 --- Throughput Derivation --- p.31 / Chapter 5.1.2 --- Throughput Analysis --- p.32 / Chapter 5.1.3 --- Convergence of S --- p.36 / Chapter 5.2 --- Infinite Population Model --- p.38 / Chapter 5.2.1 --- Attempt Rate --- p.38 / Chapter 5.2.2 --- Asymptotic Throughput of Non-carrier-sensing System --- p.39 / Chapter Chapter 6 --- Carrier-sensing System --- p.43 / Chapter 6.1 --- Throughput Derivation --- p.43 / Chapter 6.2 --- Asymptotic Behavior --- p.44 / Chapter Chapter 7 --- General MPR Model --- p.48 / Chapter Chapter 8 --- Conclusions --- p.51 / Bibliography --- p.53

Jiang Libin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 84-87). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivations and Contributions --- p.1 / Chapter 1.2 --- Related Works --- p.3 / Chapter 1.3 --- Organization of the Thesis --- p.4 / Chapter Chapter 2 --- Background --- p.6 / Chapter 2.1 --- IEEE 802.11 --- p.6 / Chapter 2.1.1 --- Basics of 802.11 Standard --- p.6 / Chapter 2.1.2 --- Types of Networks --- p.10 / Chapter 2.1.3 --- Automatic Repeat request (ARQ) in 802.11b --- p.11 / Chapter 2.2 --- Hidden- and Exposed-node Problems --- p.15 / Chapter Chapter 3 --- Physical Interference Constraints and Protocol Constraints --- p.19 / Chapter 3.1 --- Protocol-independent Physical Interference Constraints --- p.19 / Chapter 3.2 --- Protocol-specific Physical Interference Constraints --- p.21 / Chapter 3.3 --- Protocol Collision-Prevention Constraints in 802.11 --- p.22 / Chapter 3.3.1 --- Transmitter-Side Carrier-Sensing Constraints --- p.22 / Chapter 3.3.2 --- Receiver-Side Carrier Sensing Constraints --- p.24 / Chapter Chapter 4 --- Formal Definitions of EN and HN Using a Graph Model --- p.27 / Chapter Chapter 5 --- Selective Disregard of NAVs (SDN) --- p.36 / Chapter 5.1 --- SDN. I - Turning off Physical Carrier Sensing and Using Receiver Restart Mode --- p.38 / Chapter 5.2 --- SDN.II - Selective Disregard of NAV (SDN) --- p.38 / Chapter 5.3 --- SDN.III - Constructing s-graph using Power Exchange Algorithm (PE) --- p.40 / Chapter Chapter 6 --- EN and Its Impact on Scalability --- p.42 / Chapter 6.1 --- Validation of SDN by NS-2 Simulations --- p.43 / Chapter 6.2 --- Scalability of SDN --- p.46 / Chapter 6.3 --- Non-Scalability of 802.11 --- p.47 / Chapter Chapter 7 --- Hidden-node Free Design (HFD) --- p.51 / Chapter 7.1 --- HFD for IEEE 802.11 Basic Access Mode --- p.52 / Chapter 7.1.1 --- HFD for basic access mode --- p.52 / Chapter 7.1.2 --- Proof of the HN-free property --- p.56 / Chapter 7.2 --- HFD for IEEE 802.11 RTS/CTS Access Mode --- p.59 / Chapter Chapter 8 --- Performance Evaluation of HFD --- p.62 / Chapter 8.1 --- HFD for Basic Access Mode --- p.62 / Chapter 8.2 --- HFD for RTS/CTS Access Mode --- p.64 / Chapter Chapter 9 --- Combination of SDN and HFD --- p.68 / Chapter Chapter 10 --- Conclusion --- p.75 / Appendices --- p.78 / References --- p.84

Ng Ping-chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 71-72). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview and Motivation --- p.1 / Chapter 1.2 --- Background of Offered Load Control --- p.2 / Chapter 1.3 --- Background of Stability Control --- p.3 / Chapter 1.4 --- Organization of the Thesis --- p.4 / Chapter Chapter 2 --- Performance Problems and Solutions --- p.6 / Chapter 2.1 --- Simulation Set-up --- p.6 / Chapter 2.2 --- High Packet-Drop Rate --- p.7 / Chapter 2.3 --- Re-routing Instability --- p.8 / Chapter 2.3.1 --- Hidden-Node Problem --- p.8 / Chapter 2.3.2 --- Ineffectiveness of Solving Hidden-Node Problem with RTS/CTS …… --- p.9 / Chapter 2.4 --- Solutions to High-Packet Loss Rate and Re-routing Instability --- p.10 / Chapter 2.4.1 --- Link-Failure Re-routing --- p.11 / Chapter 2.4.2 --- Controlling Offered Load --- p.13 / Chapter 2.5 --- Verification of Simulation Results with Real-life Experimental Measurements --- p.14 / Chapter Chapter 3 --- Offered Load Control --- p.16 / Chapter 3.1 --- Capacity Limited by the Hidden-node and Exposed-node Problems --- p.16 / Chapter 3.1.1 --- Signal Capture --- p.18 / Chapter 3.1.2 --- Analysis of Vulnerable Period induced by Hidden Nodes --- p.20 / Chapter 3.1.3 --- Analysis of Vulnerable Period induced by Exposed Nodes --- p.21 / Chapter 3.1.4 --- Sustainable Throughput --- p.22 / Chapter 3.2 --- Capacity Limited by Carrier Sensing Property --- p.23 / Chapter 3.3 --- Numerical Results --- p.26 / Chapter 3.4 --- General Throughput Analysis of a Single Multi-hop Traffic Flow --- p.29 / Chapter 3.5 --- Throughput Analysis on Topologies with Variable Distances between Successive Nodes --- p.31 / Chapter Chapter 4 --- Discussions of Other Special Cases --- p.33 / Chapter 4.1 --- A Carrier-sensing Limited Example --- p.33 / Chapter 4.2 --- A Practical Solution to Improve Throughput --- p.34 / Chapter Chapter 5 --- Achieving Fairness in Other Network Topologies --- p.36 / Chapter 5.1 --- Lattice Topology --- p.36 / Chapter Chapter 6 --- Stability Control --- p.39 / Chapter 6.1 --- Ad-hoc routing protocols --- p.39 / Chapter 6.2 --- Proposed scheme --- p.40 / Chapter 6.2.1 --- Original AODV --- p.41 / Chapter 6.2.2 --- AODV with Proposed Scheme --- p.42 / Chapter 6.2.2.1 --- A Single Flow in a Single Chain of Nodes --- p.43 / Chapter 6.2.2.2 --- Real-break Case --- p.44 / Chapter 6.3 --- Improvements --- p.45 / Chapter Chapter 7 --- Impacts of Data Transmission Rate and Payload Size --- p.48 / Chapter 7.1 --- Signal Capture --- p.48 / Chapter 7.2 --- Vulnerable region --- p.50 / Chapter Chapter 8 --- Performance Enhancements in Multiple Flows --- p.53 / Chapter 8.1 --- Impacts of Re-routing Instability in Two Flow Topology --- p.53 / Chapter 8.2 --- Impacts of Vulnerable Periods in Multiple Flow Topologies --- p.55 / Chapter 8.2.1 --- The Vulnerable Period induced by Individual Hidden-terminal Flow --- p.57 / Chapter 8.2.2 --- The Number of Hidden-terminal Flows --- p.58 / Chapter 8.2.3 --- Correlation between Hidden-terminal Flows --- p.60 / Chapter Chapter 9 --- Conclusion --- p.63 / Chapter Appendix A: --- General Throughput Analysis of a Single Multi-hop Traffic Flow --- p.67 / Chapter A.l --- Capacity Limited by Hidden-node and Exposed-Node --- p.67 / Chapter A.1.1 --- Sustainable Throughput --- p.68 / Chapter A.2 --- Capacity Limited by Carrier Sensing Property --- p.68 / Bibliography --- p.71

Hui, Tan Hing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 151-162). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.7 / Chapter 2.1 --- Background --- p.7 / Chapter 2.1.1 --- "Tools for Analyzing Vehicles' Speeds, Traffic Flows and Densities" --- p.7 / Chapter 2.1.2 --- Tools for Analyzing Bytes Received by the Vehicles from an AP --- p.9 / Chapter 2.1.3 --- Effort-Fairness vs Outcome-Fairness --- p.10 / Chapter 2.1.4 --- Quantifying Fairness on the Bytes Received by the Vehicles from an AP --- p.10 / Chapter 2.2 --- Delay-Tolerant Networks(DTNs) --- p.12 / Chapter 2.3 --- Drive-thru Internet Systems --- p.14 / Chapter 2.4 --- Resource Allocation/Scheduling in Drive-thru Internet and Related Systems --- p.20 / Chapter 2.4.1 --- Resource Allocation/Scheduling Algorithms for Multiple Vehicles --- p.20 / Chapter 2.4.2 --- Rate Adaptation Algorithms for Fast-varying Channels due to Vehicular Movement/Mobility --- p.29 / Chapter 3 --- Performance Evaluation of Round-robin Scheduler with IEEE 802.11 MAC --- p.33 / Chapter 3.1 --- System Model --- p.34 / Chapter 3.2 --- Description of the Real-life Vehicular Traffic Trace --- p.36 / Chapter 3.2.1 --- Analysis on Hourly Single-lane Traffic Flow of 1-80 Highway --- p.40 / Chapter 3.2.2 --- Analysis on Hourly Directional Traffic Flow of 1-80 Highway --- p.43 / Chapter 3.2.3 --- Analysis on Hourly Single-lane Vehicles' Speeds of 1-80 Highway --- p.45 / Chapter 3.2.4 --- Analysis on Daily Vehicles' Speeds of 1-80 Highway --- p.48 / Chapter 3.2.5 --- "Relationship among Average Traffic Densities, Flows and Vehicles' Speeds in Singlelane Scenarios" --- p.51 / Chapter 3.2.6 --- "Relationship among Average Traffic Densities, Flows and Vehicles' Speeds in Multilane Scenarios" --- p.52 / Chapter 3.3 --- Trace-driven Simulations of Drive-thru Internet Scenarios using Round-robin Scheduler with IEEE 802.11 MAC --- p.54 / Chapter 3.3.1 --- Simulation Setup --- p.54 / Chapter 3.3.2 --- Scenarios of using Fixed Data Rate --- p.57 / Chapter 3.3.3 --- Scenario of using Auto-rate Algorithm --- p.67 / Chapter 4 --- The Design and Implementation of VECADS --- p.73 / Chapter 4.1 --- Towards the Design of an Intelligent Scheduling for Drive-thru Internet --- p.74 / Chapter 4.1.1 --- System Throughput Maximization vs Fairness --- p.74 / Chapter 4.1.2 --- Antenna --- p.75 / Chapter 4.1.3 --- Speed --- p.76 / Chapter 4.1.4 --- Noisy Measurement of Predicting Channel Condition based on RSSI(or Similar Metrics) only --- p.77 / Chapter 4.1.5 --- Region for Serving “Weak´ح Vehicles --- p.78 / Chapter 4.2 --- System Model --- p.79 / Chapter 4.3 --- The Design of VECADS --- p.83 / Chapter 4.3.1 --- Using Vehicular Context to Help Scheduling --- p.83 / Chapter 4.3.2 --- Penalizing Slow Vehicles in the Coverage . --- p.88 / Chapter 4.3.3 --- "Round-Robin Scheduling for ""Weak"" Vehicles in the “Sweet Zone´ح" --- p.90 / Chapter 4.3.4 --- Rate Adaptation Algorithm in VEC ADS --- p.94 / Chapter 4.4 --- The Implementation of VECADS --- p.97 / Chapter 4.4.1 --- Overall System Architecture of VECADS --- p.97 / Chapter 4.4.2 --- Overall Scheduling Flow of VECADS --- p.100 / Chapter 4.4.3 --- Algorithms in VECADS --- p.102 / Chapter 5 --- Performance Evaluation of VECADS --- p.110 / Chapter 5.1 --- Simulation Setup --- p.110 / Chapter 5.2 --- Simulation Results and Discussion --- p.114 / Chapter 5.2.1 --- Evaluation of the Performance Impact of Different System Parameters --- p.114 / Chapter 5.2.2 --- Evaluation of Different Design Options --- p.119 / Chapter 6 --- Conclusions and Discussion --- p.142 / Chapter A --- Average Bytes Received by a Moving Vehicle from a Roadside AP --- p.146 / Chapter B --- Distribution of the Cumulative Bytes Received by Vehicles from a Roadside AP --- p.148 / Bibliography --- p.151

Based on the above scheme, we propose a number of solutions to reduce the computational complexity and communication cost. To reduce the computational complexity, we propose to aggregate the local data and transit data and route them with a single set of routing variables. To reduce the communication overhead, a different smoothing function is proposed that only requires the information of a set of bottleneck nodes. The optimality conditions are derived and a distributed algorithm is designed accordingly. Simulation results illustrate the effectiveness and efficiency of the proposed solution. / Sleeping scheduling is another approach to save energy consumption for sensor networks. The basic idea is to schedule the duty-cycles of sensor nodes such that off-duty sensors are turned off as long as the network functionality can be maintained by working nodes. For applications whereby coordination of sleeping among sensors is not possible or inconvenient, random sleeping is the only option. We present the Asynchronous Random Sleeping (ARS) scheme whereby sensors (i) do not need to synchronize with each other, and (ii) do not need to coordinate their wakeup patterns. The stationary coverage probability and the expected coverage periods for ARS are derived. For surveillance application, we derive in addition the detection probability and detection delay distribution. We find that the expected detection delay of asynchronous random sleeping is smaller than that of the synchronous random sleeping. / This thesis is focused on the design and analysis of energy conservation methods for wireless sensor networks (WSNs). Unlike traditional wireless networks, sensor nodes in WSNs are collaborating towards a common mission. The failure of some sensor nodes may cause significant topological changes and loss of information at the target region. Therefore, network lifetime is the primary objective for designing energy conservation solutions for WSNs. / We address the energy conservation problem from the aspects of maximum lifetime routing, data aggregation and sleeping scheduling. We first propose a data aggregated maximum lifetime routing scheme for wireless sensor networks. We adopt a data aggregation model that decouples the routing of local data and transit data. The objective is to jointly optimize data aggregation and routing so that the network lifetime can be maximized. A recursive smoothing method is adopted to overcome the nondifferentiability of the objective function. We derive the necessary and sufficient conditions for achieving the optimality of the smoothing function and design a distributed gradient algorithm accordingly. We show that the proposed scheme can significantly reduce the data traffic and improve the network lifetime. The distributed algorithm can converge to the optimal value efficiently under all network configurations. / Hua Cunqing. / "June 2006." / Adviser: Tak-Shing Yum. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1825. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 120-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Nam Chung Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 68-71). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview and Motivation --- p.1 / Chapter 1.2 --- Organization of the Thesis --- p.5 / Chapter Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Basics of 802.11 Standard --- p.6 / Chapter 2.1.1 --- Distributed Coordination Function (DCF) / Point Coordination Function (PCF) --- p.7 / Chapter 2.1.2 --- RTS/CTS --- p.8 / Chapter 2.2 --- Types of Networks --- p.9 / Chapter 2.3 --- Automatic Repeat request (ARQ) in 802.11b --- p.11 / Chapter 2.3.1 --- Importance of Link-layer ARQ in Wireless Networks --- p.12 / Chapter 2.3.2 --- MAC Algorithm of 802.11b Standard --- p.13 / Chapter 2.3.3 --- Modified MAC algorithm in 802.11b commercial products --- p.14 / Chapter 2.4 --- Automatic Adjustment of Radio Data Rate in Commercial 802.11b Products --- p.15 / Chapter Chapter 3 --- Head-of-Line Blocking in Access Points --- p.17 / Chapter 3.1 --- Cause of HOL blocking in 802.11b --- p.17 / Chapter 3.1.1 --- Calculation of Worst-Case Service Time for Packet at Head of Queue --- p.19 / Chapter 3.2 --- Simulation Settings --- p.21 / Chapter 3.2.1 --- Propagation Models Available in NS2 --- p.21 / Chapter 3.2.2 --- Variables of Shadowing Model --- p.25 / Chapter 3.3 --- Simulation Results on UDP --- p.26 / Chapter 3.4 --- Experimental Results on UDP --- p.28 / Chapter 3.5 --- Simulation Results on TCP --- p.32 / Chapter 3.6 --- Experimental Results on TCP --- p.34 / Chapter 3.7 --- Possible Solutions of HOL Blocking Problem --- p.35 / Chapter 3.7.1 --- Weakening Link-layer ARQ in 802.11b --- p.36 / Chapter 3.7.2 --- Effectiveness of ARQ in 802.11b --- p.37 / Chapter 3.7.2.1 --- Set-up for Network Experiments --- p.38 / Chapter 3.7.2.2 --- Results and Analysis --- p.39 / Chapter 3.7.3 --- Virtual Queuing --- p.45 / Chapter Chapter 4 --- Study of Uplink Traffic --- p.50 / Chapter 4.1 --- Poor Pulling Down the Rich --- p.51 / Chapter 4.2 --- Signal Capturing Effect --- p.53 / Chapter 4.2.1 --- Mathematical Analysis of Signal Capturing Effect --- p.55 / Chapter Chapter 5 --- Packet Loss Patterns in 802.11b WLAN --- p.61 / Chapter 5.1 --- """Random Loss"" vs ""Bursty Loss""" --- p.61 / Chapter 5.2 --- Experimental Evaluation --- p.62 / Chapter Chapter 6 --- Conclusion --- p.65 / Bibliography --- p.68

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Chan, Hing Pan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 107-109). / Abstracts in English and Chinese. / Chapter Chapter 1 - --- Introduction --- p.1 / Chapter Chapter 2 - --- Background --- p.3 / Chapter 2.1 --- IEEE 802.11 MAC Protocol --- p.3 / Chapter 2.2 --- Related Work --- p.5 / Chapter Chapter 3 - --- Design Principles --- p.8 / Chapter Chapter 4 - --- Load-Adaptive Transmission Scheduling --- p.11 / Chapter 4.1 --- Contention Period (CP) --- p.14 / Chapter 4.2 --- Service Period (SP) --- p.22 / Chapter Chapter 5 - --- Synchronization --- p.27 / Chapter 5.1 --- Slot Boundary Detection --- p.27 / Chapter 5.2 --- Period Boundary Detection --- p.29 / Chapter 5.3 --- Period Identification --- p.30 / Chapter 5.4 --- Exception Handling --- p.62 / Chapter Chapter 6 - --- Performance Analysis --- p.70 / Chapter Chapter 7 - --- Performance Evaluations --- p.73 / Chapter 7.1 --- Parameter Tuning --- p.75 / Chapter 7.2 --- CBR UDP Traffic --- p.82 / Chapter 7.3 --- TCP Traffic --- p.94 / Chapter 7.4 --- Performance in Multi-hop Networks --- p.101 / Chapter Chapter 8 - --- Conclusions --- p.105 / Bibliography --- p.107

The prevalence of wireless networks is on the increase. Society is becoming increasingly reliant on ubiquitous computing, where mobile devices play a key role. The use of wireless networking is a natural solution to providing connectivity for such devices. However, the availability of infrastructure in wireless networks is often limited. Such networks become dependent on wireless ad hoc networking, where nodes communicate and form paths of communication themselves. Wireless ad hoc networks present novel challenges in contrast to fixed infrastructure networks. The unpredictability of node movement and route availability become issues of significant importance where reliability is desired.To improve reliability in wireless ad hoc networks, predicting future connectivity between mobile devices has been proposed. Predicting connectivity can be employed in a variety of routing protocols to improve route stability and reduce unexpected drop-offs of communication. Previous research in this field has been limited, with few proposals for generating future predictions for mobile nodes. Further work in this field is required to gain a better insight into the effectiveness of various solutions.This thesis proposes such a solution to increase reliability in wireless ad hoc routing. This research presents two novel concepts to achieve this: the Communication Map (CM), and the Future Neighbours Table (FNT). The CM is a signal loss mapping solution. Signal loss maps delineate wireless signal propagation capabilities over physical space. With such a map, connectivity predictions are based on signal capabilities in the environment in which mobile nodes are deployed. This significantly improves accuracy of predictions in this and in previous research. Without such a map available, connectivity predictions have no knowledge of realistic spatial transmission ranges. The FNT is a solution to provide routing algorithms with a predicted list of future periods of connectivity between all nodes in an established wireless ad hoc network. The availability of this information allows route selection in routing protocols to be greatly improved, benefiting connectivity. The FNT is generated from future node positional information combined with the CM to provide predicted signal loss estimations at future intervals. Given acceptable signal loss values, the FNT is constructed as a list of periods of time in which the signal loss between pairs of nodes will rise above or fall below this acceptable value (predicted connectivity). Future node position information is ideally found in automated networks. Robotic nodes commonly operate where future node task movement is developed and planned into the future, ideal for use in predicted connectivity. Non-automated prediction is also possible, as there exist some situations where travel paths can be predictable, such as mobile users on a train or driving on a highway. Where future node movement is available, predictions of connectivity between nodes are possible.