Sze, Kam Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 49-53). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

本文研究面向可靠的無線傳感器網絡的協議設計，測試和診斷。 / 在協議設計方面，我們集中研究媒體接入層的協議設計。首先，我們為水下無線傳感器網絡提出一個有效的媒體接入層協議RAS 。這個協議利用了水下無線傳感器網絡和地面無線傳感器網絡的媒體傳輸時延的差別，采用了並行傳輸的優先級方法。由于會導致碰撞，這種並行傳輸的方法不能被用在地面無線傳感器網絡中。該方法為高負荷的傳感器節點分配更長的傳輸時間。這種具有優先級的機制也同時提高了公平方面的性能。第二，我們處理水下無線傳感器網絡中由于報文失導致的不可靠的問題。基于之前提出的協議RAS ，我們提出了可靠的RAS 協議。該協議可以在可靠性和有效性方便達到一個平衡。它里面的報文確認和重傳機制同傳統的方法不同，所以它可以在提高可靠性的同時保證吞吐量不會被大幅降低。 / 第三，在協議測試方面，我們設計了RealProct ，一種新的可靠的用于無線傳感器網絡的一致性協議測試(測試協議實現是否符合協議規範)的架構。RealProct 采用了實際的傳感器節點來保證測試盡可能的接近實際部署。為了節省使用大規模實際部署來測試的硬件成本和控制成本， RealProct 使用少量傳感器節點虛擬各樣的拓撲結構和事件。同時，測試執行和裁決算法也用于最小化測試用例執行次數，並保證假陰和假陽錯誤低于給定值。 / 最後，我們提出了MDiag，一種使用移動智能手機巡視無線傳感器網絡並診斷網絡錯誤的方法。由于該智能手機不是無線傳感器網絡的組成部分，因此該診斷不會像其它已有的診斷方法那樣影響原無線傳感器網絡的運行。並且，使用智能手機巡視並診斷無線傳感器網絡比部署另一個用于診斷的網絡更有效。在巡視過程中，無線傳感器網絡所交互的報文被收集起來，然後被我們所設計的報文解析器所分析。然後，我們設計了統計性規則來指導異常現象的診斷。為了提高巡視效率，我們提出了一個巡視方法MSEP。 / 我們做了大量實驗驗證以上提出的方法和算法，結果表明它們在達到可靠性無線傳感器網絡的目標上很有效。 / This thesis investigates the protocol design, testing, and diagnosis of Wireless Sensor Networks (WSNs) to achieve dependable WSNs. / In the aspect of protocol design, we focus on the MAC (Medium Access Control) layer protocol design. First, we propose an efficient MAC protocol RAS (routing and application based scheduling protocol) for underwater acoustic sensor networks (UWASNs), a type of WSNs that are deployed in the water. Utilizing the medium propagation difference between UWASNs and terrestrial wireless sensor networks (TWSNs), RAS performs parallel transmissions which would definitely result in collisions in TWSNs. It schedules the transmissions with different priorities by allocating longer time to heavier-traffic sensor nodes. The priority mechanism also benefits the fairness performance. Second, we tackle the unreliability problem caused by the packet loss in UWASNs. Based on the previously designed RAS, we propose a reliable RAS called RRAS that obtains a tradeoff between the reliability and the efficiency. RRAS applies an ACK and retransmission mechanism that is different from the traditional one, so that it can maintain a comparable throughput while improving reliability. / Third, in the area of protocol testing, we design RealProct (reliable Protocol conformance testing with Real sensor nodes), a novel and reliable framework for performing protocol conformance testing in WSNs, i.e., testing the protocol implementations against their specifications. With real sensor nodes, RealProct can ensure that the testing scenarios are as close to the real deployment as possible. To save the hardware cost and control efforts required by testing with large-scale real deployments, RealProct virtualizes a network with any topology and generates non-deterministic events using only a small number of sensor nodes. In addition, test execution and verdict are optimized to minimize the number of test case runs, while guaranteeing satisfactory false positive and false negative rates. / Finally, we propose MDiag, a Mobility-assisted Diagnosis approach that employs smartphones to patrol the WSNs and diagnose failures. Diagnosing with a smartphone which is not a component of WSNs does not intrude the execution of the WSNs as most of the existing diagnosis methods. Moreover, patrolling the smartphone in the WSNs to investigate failures is more efficient than deploying another diagnosis network. During the patrol, packets exchanged in the WSNs are collected and then analyzed by our implemented packet decoder. Statistical rules are also designed to guide the detection of abnormal cases. Aiming at improving the patrol efficiency, a patrol approach MSEP (maximum snooping efficiency patrol) is proposed. We compare MSEP with a naive method, the greedy method, and a baseline method, and demonstrate that MSEP is better in increasing the detection rate and reducing the patrol time than other methods. / We perform extensive evaluations to verify the proposed techniques and algorithms, and the results confirm their advantages in achieving dependable WSNs. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Xiong, Junjie. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 136-154). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction and Background Study --- p.1 / Chapter 1.1 --- Wireless Sensor Networks (WSNs) --- p.1 / Chapter 1.1.1 --- Sensor Node --- p.5 / Chapter 1.1.2 --- The Base Station (BS) --- p.8 / Chapter 1.1.3 --- The Operating System (OS) of the Sensor Node --- p.8 / Chapter 1.1.4 --- The Protocol Design of WSNs --- p.11 / Chapter 1.2 --- Thesis Scope and Contributions --- p.20 / Chapter 1.2.1 --- Protocol Design --- p.20 / Chapter 1.2.2 --- Protocol Testing --- p.22 / Chapter 1.2.3 --- Protocol Diagnosis --- p.23 / Chapter 1.3 --- Thesis Organization --- p.23 / Chapter 2 --- An Efficient MAC Protocol Design --- p.25 / Chapter 2.1 --- Introduction --- p.26 / Chapter 2.2 --- Related Work --- p.28 / Chapter 2.3 --- RAS Overview --- p.29 / Chapter 2.3.1 --- Scheduling Element --- p.32 / Chapter 2.4 --- The Scheduling Problem in UWASNs --- p.34 / Chapter 2.4.1 --- Scheduling Principles --- p.34 / Chapter 2.4.2 --- Scheduling Problem Formulation --- p.35 / Chapter 2.4.3 --- Scheduling Problem Analysis --- p.37 / Chapter 2.5 --- RAS Protocol --- p.38 / Chapter 2.5.1 --- Scheduling Algorithm of the RAS Protocol --- p.38 / Chapter 2.5.2 --- Analysis of the RAS Protocol --- p.39 / Chapter 2.6 --- Performance Evaluation --- p.42 / Chapter 2.6.1 --- Schedule Length --- p.42 / Chapter 2.6.2 --- Network Throughput --- p.44 / Chapter 2.6.3 --- Average End-to-end Delay --- p.46 / Chapter 2.6.4 --- Average Maximum Queue Length per Node --- p.47 / Chapter 2.7 --- Discussions and Conclusions --- p.49 / Chapter 3 --- A Reliable MAC Protocol Design --- p.51 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Related Work --- p.54 / Chapter 3.3 --- RRAS Protocol --- p.55 / Chapter 3.3.1 --- Overview of NACK-retransmission Mechanism --- p.56 / Chapter 3.3.2 --- Retransmission Mechanism --- p.57 / Chapter 3.3.3 --- Retransmission Time --- p.59 / Chapter 3.4 --- Performance Evaluation --- p.61 / Chapter 3.4.1 --- Retransmission Time of RRAS --- p.62 / Chapter 3.4.2 --- Working Time of RRAS and RAS --- p.63 / Chapter 3.4.3 --- Success Rate of RRAS and RAS --- p.64 / Chapter 3.4.4 --- Throughput of RRAS and RAS --- p.65 / Chapter 3.5 --- Conclusions --- p.66 / Chapter 4 --- Reliable Protocol Conformance Testing --- p.67 / Chapter 4.1 --- Introduction --- p.68 / Chapter 4.2 --- Related Work --- p.71 / Chapter 4.3 --- Protocol Conformance Testing --- p.73 / Chapter 4.3.1 --- PCT Process --- p.74 / Chapter 4.3.2 --- PCT Architecture --- p.75 / Chapter 4.4 --- Design of the RealProct Framework --- p.76 / Chapter 4.5 --- RealProct Techniques --- p.79 / Chapter 4.5.1 --- Topology Virtualization --- p.80 / Chapter 4.5.2 --- Event Virtualization --- p.81 / Chapter 4.5.3 --- Dynamic Test Execution --- p.85 / Chapter 4.6 --- Generality of RealProct --- p.88 / Chapter 4.7 --- Evaluation --- p.89 / Chapter 4.7.1 --- Detecting New Bugs in TCP --- p.90 / Chapter 4.7.2 --- Detecting Previous Bugs in TCP --- p.94 / Chapter 4.7.3 --- Testing Routing Protocol RMRP --- p.98 / Chapter 4.8 --- Conclusions --- p.99 / Chapter 5 --- Mobility-assisted Diagnosis for WSNs --- p.101 / Chapter 5.1 --- Introduction --- p.102 / Chapter 5.2 --- Related Work --- p.105 / Chapter 5.3 --- MDiag Background --- p.108 / Chapter 5.3.1 --- Network Architecture --- p.108 / Chapter 5.3.2 --- Failure Classification --- p.108 / Chapter 5.4 --- MDiag Framework --- p.109 / Chapter 5.4.1 --- Packet Decoder Input and Output --- p.111 / Chapter 5.4.2 --- Statistical Rules on Packet Analysis --- p.112 / Chapter 5.5 --- Coverage-oriented Smartphone Patrol Algorithms --- p.115 / Chapter 5.5.1 --- Naive Method (NM) --- p.115 / Chapter 5.5.2 --- Greedy Method (GM) --- p.116 / Chapter 5.5.3 --- Maximum Snooping Efficiency Patrol (MSEP) --- p.118 / Chapter 5.6 --- Evaluations --- p.119 / Chapter 5.6.1 --- Permanent Failure Detection --- p.121 / Chapter 5.6.2 --- Short-term Failure Detection --- p.122 / Chapter 5.7 --- Conclusions --- p.130 / Chapter 6 --- Conclusions --- p.132 / Bibliography --- p.136

Recent advances in micro-electro-mechanical systems (MEMS) fabrication have made it possible to construct miniature devices containing an embedded system with strong computing capabilities. New generations of low cost sensor nodes can be created small with powerful computing and sensing capabilities. The small sensor nodes together with distributed wireless networking techniques enable the creation of innovative self-organized and peer-to-peer large scale wireless sensor networks (WSNs). A coordinated network of sensor nodes can perform distributed sensing of environmental phenomena over large-scale physical spaces and enable reliable monitoring and control in various applications. WSNs provide bridges between the virtual world of information technology and the real physical world. They represent a fundamental paradigm shift from traditional inter-human personal communications to autonomous inter-device communications. This thesis investigates the problems of target detection and tracking in WSNs. WSNs have some unique advantages over traditional sensor networks. However, the severe scarcity of power, communication and computation resources imposes some major challenges on the design and applications of distributed protocols for WSNs. In particular, this thesis focuses on two aspects of remote target detection and tracking in WSNs: distributed source coding (DSC) and sensor node localization. The primary purpose is to improve the application performance while minimizing energy consumption and bandwidth overhead.

This document presents the Centralized Energy Management System (CEMS), a dynamic fault-tolerant reclustering protocol for wireless sensor networks. CEMS reconfigures a homogeneous network both periodically and in response to critical events (e.g. cluster head death). A global TDMA schedule prevents costly retransmissions due to collision, and a genetic algorithm running on the base station computes cluster assignments in concert with a head selection algorithm. CEMS' performance is compared to the LEACH-C protocol in both normal and failure-prone conditions, with an emphasis on each protocol's ability to recover from unexpected loss of cluster heads.

The purpose of this dissertation was to develop, validate, and implement multi-sensor approaches for measuring physical activity and social/contextual covariates in 2-5 year-old children via wearable-, wireless communication-, and infrared-depth camera-based technologies. In Chapter 2, a three-phased study design was used to validate a method for estimating metered distances between wearable devices using accelerometer-derived Bluetooth signals. Results showed that distances, up to 20 meters, can be predicted between a single Bluetooth beacon and receiver using a Random Forest algorithm. When multiple Bluetooth beacons and receivers were used within the same environment, a moving average filter was required to recover observations lost due to noise. Overall, simulation and validation data suggest that accelerometer-derived Bluetooth signals can be used in studies of physical activity co-participation to 1) estimate metered distances between devices using a single beacon-receiver paradigm, as well as to 2) estimate the proportion of time that devices are proximal when using multiple beacons and receivers. Chapter 3 characterized the relationship between objectively measured physical activity and dyadic spatial proximities in 2 year-olds and their parents. Data revealed that the overall proportions of time that children and their parents spent in total physical activity were positively associated, and time series data revealed that this relationship remained consistent when analyzed hour-to-hour. Time spent engaged in sedentary behavior was also positively associated between children and parents; however, there was no association between child and parent moderate-vigorous physical activity volumes. Dyadic proximity results showed that girls spent more time in joint physical activity with their mothers than boys. Furthermore, children who engaged in >60 minutes of daily moderate-vigorous physical activity spent an additional 30 minutes in joint total physical activity with their mothers each day, on average, when compared to children who engaged in <60 minutes of daily moderate-vigorous physical activity. Finally, boys and girls who engaged in >60 minutes of daily moderate-vigorous physical activity participated in joint physical activity with their mothers across wider relative distances, on average, than did boys who engaged in physical activity at closer relative distances to their mothers. In Chapter 4, an original computer vision algorithm was applied to infrared-depth camera data for the purpose of converting three-dimensional videos into triaxial physical activity signals in young children. Physical activity data were collected in 2-5 year-old children during 20-minute semi-structured, indoor child-parent dyadic play sessions. Play session video data were converted into triaxial physical activity signals using a multi-phased computer vision algorithm for each child. Computer vision-derived triaxial physical activity cut points for 2-5 year-olds were calibrated against a direct observation reference system using a machine learning algorithm. Results revealed that triaxial activity signals, as measured by a dual-sensor camera, can be used to estimate both physical activity intensities and volumes in young children without the use of wearable technology. Collectively, these studies show that multi-sensor approaches to physical activity measurement are a valid means by which to measure physical activity and social/contextual covariates in young children using either wearable sensors or computer vision.

Ng Tsz Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 67-70). / Abstracts in English and Chinese. / ABSTRACT --- p.i / 摘要 --- p.ii / ACKNOWLEDGEMENTS --- p.iii / LIST OF FIGURES --- p.iv / LIST OF TABLES --- p.ix / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Literature Review --- p.3 / Chapter 1.3 --- Research Objectives --- p.5 / Chapter 1.4 --- Thesis Organization --- p.5 / Chapter CHAPTER 2 --- MODELING OF PIEZOELECTRIC SENSOR/GENERATOR --- p.6 / Chapter 2.1 --- Constitutive Equations --- p.6 / Chapter 2.2 --- Voltage Output of Piezoelectric Materials --- p.9 / Chapter 2.2.1 --- Short Circuit --- p.9 / Chapter 2.2.2 --- Open Circuit --- p.11 / Chapter 2.3 --- Sensitivity and Power Generation --- p.13 / Chapter 2.4 --- Modeling and Analysis of Sensor Structure --- p.23 / Chapter 2.4.1 --- Damping Ratio Estimation --- p.25 / Chapter (a) --- Half-power bandwidth method --- p.25 / Chapter (b) --- Linear interpolation method --- p.25 / Chapter 2.4.2 --- Trade-off between Resonant Frequency and Output Sensitivity of a Sensor --- p.29 / Chapter (a) --- Maximize Sme with constant wn --- p.31 / Chapter (b) --- Maximize wn with constant Sme --- p.33 / Chapter 2.5 --- Model Accuracy --- p.39 / Chapter CHAPTER 3 --- POWER HARVESTING --- p.41 / Chapter 3.1 --- Circuit Model --- p.41 / Chapter 3.2 --- Energy Storage --- p.47 / Chapter 3.3 --- Size Effect on Power Output --- p.49 / Chapter 3.4 --- Power Harvesting Circuit --- p.50 / Chapter 3.4.1 --- Performance of the Power Harvesting Circuit --- p.51 / Chapter (a) --- Power Harvesting Circuit Efficiency --- p.52 / Chapter (b) --- Useful Power Output --- p.53 / Chapter (c) --- System Efficiency --- p.56 / Chapter (d) --- Relationship between Input Excitation and Charge Time --- p.57 / Chapter 3.5 --- Harvested Energy for Wireless Transmission --- p.60 / Chapter CHAPTER 4 --- CONCLUDING REMARKS --- p.64 / Chapter 4.1 --- Sensor/Generator Design --- p.64 / Chapter 4.2 --- Potential Applications --- p.64 / Chapter 4.3 --- Conclusion --- p.65 / Chapter 4.4 --- Future Work --- p.66 / REFERENCES --- p.67 / APPENDIX --- p.71

Lee Lok Hang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 87-93). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Sensors and Sensor Networks --- p.3 / Chapter 1.2 --- Sensor Network Deployment --- p.7 / Chapter 1.3 --- Motivations --- p.7 / Chapter 1.4 --- Contributions --- p.9 / Chapter 1.5 --- Thesis Organization --- p.10 / Chapter 2 --- Literature Review --- p.11 / Chapter 2.1 --- Data Cube --- p.11 / Chapter 2.2 --- Data Aggregation in Sensor Networks --- p.12 / Chapter 2.2.1 --- Hierarchical Data Aggregation --- p.13 / Chapter 2.2.2 --- Gossip-based Aggregation --- p.13 / Chapter 2.2.3 --- Hierarchical Gossip Aggregation --- p.13 / Chapter 2.3 --- GAF Algorithm --- p.14 / Chapter 2.4 --- Concurrency Control --- p.17 / Chapter 2.4.1 --- Two-phase Locking --- p.17 / Chapter 2.4.2 --- Timestamp Ordering --- p.18 / Chapter 3 --- Building Distributed Data Cubes in Sensor Network --- p.20 / Chapter 3.1 --- Aggregation Operators --- p.21 / Chapter 3.2 --- Distributed Prefix (PS) Sum Data Cube --- p.22 / Chapter 3.2.1 --- Prefix Sum (PS) Data Cube --- p.22 / Chapter 3.2.2 --- Notations --- p.24 / Chapter 3.2.3 --- Querying a PS Data Cube --- p.25 / Chapter 3.2.4 --- Building Distributed PS Data Cube --- p.27 / Chapter 3.2.5 --- Time Bounds --- p.32 / Chapter 3.2.6 --- Fast Aggregate Queries on Multiple Regions --- p.37 / Chapter 3.2.7 --- Simulation Results --- p.43 / Chapter 3.3 --- Distributed Local Prefix Sum (LPS) Data Cube --- p.50 / Chapter 3.3.1 --- Local Prefix Sum Data Cube --- p.52 / Chapter 3.3.2 --- Notations --- p.55 / Chapter 3.3.3 --- Querying an LPS Data Cube --- p.56 / Chapter 3.3.4 --- Building Distributed LPS Data Cube --- p.61 / Chapter 3.3.5 --- Time Bounds --- p.63 / Chapter 3.3.6 --- Fast Aggregate Queries on Multiple Regions --- p.67 / Chapter 3.3.7 --- Simulation Results --- p.68 / Chapter 3.3.8 --- Distributed PS Data Cube Vs Distributed LPS Data Cube --- p.74 / Chapter 4 --- Concurrency Control and Consistency in Sensor Networks --- p.76 / Chapter 4.1 --- Data Inconsistency in Sensor Networks --- p.76 / Chapter 4.2 --- Traditional Concurrency Control Protocols and Sensor Networks --- p.80 / Chapter 4.3 --- The Consistent Retrieval of Data from Distributed Data Cubes --- p.81 / Chapter 5 --- Conclusions --- p.85 / References --- p.87 / Appendix --- p.94 / A Publications --- p.94

No description available.

Mobile wireless sensor networks (MWSNs) will enable information systems to gather detailed information about the environment on an unprecedented scale. These selforganising, distributed networks of sensors, processors and actuators that are capable of movement have a broad range of potential applications, including military reconnaissance, surveillance, planetary exploration and geophysical mapping. In many of the foreseen applications a certain geometric pattern will be required for the task. Hence, algorithms for maintaining the geometric pattern of an MWSN are investigated. In many tasks such as land mine detection, a group of nodes arranged in a line must provide continuous coverage between each end of the formation. Thus, we present algorithms for maintaining the geometric pattern of a group of nodes arranged in a line. An MWSN may also need to form a geometric pattern without assistance from the user. In military reconnaissance, for example, the nodes will be dropped onto the battlefield from a plane and land at random positions. The nodes will be expected to arrange themselves into a predetermined formation in order to perform a specific task. Thus, we present algorithms for forming a circle and regular polygon from a given set of random positions. The algorithms are distributed and use no communication between the nodes to minimise energy consumption. Unlike past studies of geometric problems where algorithms are either tested in simulations where each node has global knowledge of all the other nodes or implemented on a small number of robots, the robustness of our algorithms has been studied with simulations that model the sensor system in detail. / The nodes locate their neighbours using simulated vision where a ray-tracer is used to generate images of a model of the scene that would be captured by each node's cameras. The simulations demonstrate that the algorithms are robust against random errors in the sensors and actuators. Even though the nodes had incomplete knowledge of the positions of other nodes due to occlusion, they were still able to perform the assigned tasks.

The development of embedded system technologies have made it feasible to deploy large-scale sensor and actuator networks. These networks are revolutionizing the way in which we understand, monitor and control complex physical environment, and provide one of the missing connections between the Internet and the physical world. Because of size, form factor and cost considerations, wireless sensor networks suffer from severe resource constraints, such as communication bandwidth and range, computation power, memory and energy. Furthermore, sensor networks are expected to consist of hundreds of sensors in the future. The resource constraints of tiny embedded devices, together with the large network size, create many research challenges which do not appear in traditional networks. In this dissertation, we address the challenges involved in designing robust and scalable sensor network system. In contrast to the flat networking model considered in previous sensor networks research, we propose a hierarchical or hybrid network architecture which is more scalable and robust. Hybrid sensor networks consist of resource-impoverished sensors and resource-rich sensors, called micro-servers. Because of the different capabilities of heterogeneous devices in hybrid sensor networks, there is need for effective deployment and utilization of network resources. Therefore, we introduce resource provisioning and management algorithms to optimize the performance of hybrid sensor networks. The first contribution of this dissertation is the design and implementation of new network architecture and algorithms to address the computation power and memory limitations of tiny embedded devices. The second contribution of this dissertation is the design and evaluation of an Anycast communication paradigm for hybrid sensor and actuator networks. We propose and evaluate a reverse tree-based Anycast mechanism tailored to deal with the unique event dynamics in sensor networks. The third contribution of this dissertation is the design and evaluation of an energy provisioning and management algorithm for hybrid sensor and actuator networks. Our studies show that the location of extra energy-provisioning can affect the lifetime of system dramatically; and hybrid sensor networks are financially cost-effective for a large number of cases which makes them a scalable solution. Together, these contributions enable effective resource provisioning and management in hybrid sensor networks.