Over the past fifteen years, advances in Micro-Electro-Mechanical Systems (MEMS) technology have enabled rapid development of wireless sensor networks (WSNs). A WSN consists of a large number of sensor nodes that are typically powered by batteries. Each sensor node collects useful information from its environment, and forwards this data to a base station through wireless communications. Applications of WSNs include environmental monitoring, industrial monitoring, agriculture, smart home monitoring, military surveillance, to name a few. Due to battery constraint at each sensor node, a fundamental challenge for a WSN is its limited operational lifetime -- the amount of time that the network can remain operational before some or all of the sensor nodes run out of battery. To conserve energy and prolong the lifetime of a WSN, there have been active research efforts across all network layers. Although these efforts help conserve energy usage and prolong network lifetime to some extent, energy and lifetime remain fundamental bottlenecks and are the key factors that hinder the wide-scale deployment of WSNs. This dissertation addresses the energy problem of a WSN by exploiting a recent breakthrough in wireless energy transfer (WET) technology. This breakthrough WET technology is based on the so-called magnetic resonant coupling (MRC), which allows electric energy to be transferred from a source coil to a receive coil without any plugs or wires. The advantages of MRC are high energy transfer efficiency even under omni-direction, not requiring line-of-sight (LOS), and being robust against environmental conditions. Inspired by this enabling WET technology, this dissertation focuses on applying MRC to a WSN and on studying how to optimally use this technology to address lifetime problem for a WSN. The goal is to fundamentally remove lifetime bottleneck for a WSN. The main contributions of this dissertation are summarized as follows: 1. Single-node Charging for a Sparse WSN. We first investigate how MRC can be applied to a WSN so as to remove the lifetime performance bottleneck in a WSN, i.e., allowing a WSN to remain operational forever. We consider the scenario of a mobile wireless charging vehicle (WCV) periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions for a sensor node to maintain its renewable energy cycle. We study an optimization problem, with the objective of maximizing the ratio of the WCV's vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and uncover a number of important properties. Subsequently, we develop a near-optimal solution by a piecewise linear approximation technique and prove its performance guarantee. This first study shows that network lifetime bottleneck can be fundamentally resolved by WET. 2. Multi-node Charging for a Dense WSN. We next exploit recent advances in MRC that allows multiple sensor nodes to be charged at the same time, and show how MRC with multi-node charging capability can address the scalability problem associated with the single-node charging technology. We consider a WCV that periodically travels inside a WSN and can charge multiple sensor nodes simultaneously. Based on the charging range of the WCV, we propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal cells. We pursue a formal optimization framework by jointly optimizing the traveling path of the WCV, flow routing among the sensor nodes, and the charging time with each hexagonal cell. By employing discretization and a novel Reformulation-Linearization Technique (RLT), we develop a provably near-optimal solution for any desired level of accuracy. Through numerical results, we demonstrate that our solution can indeed address the scalability problem for WET in a dense WSN. 3. Bundling Mobile Base Station and Wireless Energy Transfer: The Pre-planned Path Case. Our aforementioned work is based on the assumption that the location of base station is fixed and known in the WSN. On the other hand, it has been recognized that a mobile base station (MBS) can offer significant advantages over a fixed one. But employing two separate vehicles, one for WET and one for MBS, could be expensive and hard to manage. So a natural question to ask is: can we bundle WET and MBS on the same vehicle? This is the focus of this study. Here, our goal is to minimize energy consumption of the entire system while ensuring that none of the sensor nodes runs out of energy. To simplify the problem, we assume that the path for the vehicle is given a priori. We develop a mathematical model for this problem. Instead of studying the general problem formulation (called CoP-t), which is time-dependent, we show that it is sufficient to study a special subproblem (called CoP-s), which only involves space-dependent variables. Subsequently, we develop a provable near-optimal solution to CoP-s with the development of several novel techniques including discretizing a continuous path into a finite number of segments and representing each segment with worst-case energy bounds. 4. Bundling Mobile Base Station and Wireless Energy Transfer: The Unconstrained Path Case. Based on our experience for the pre-planned path case, we further study the problem where the traveling path of the WCV (also carrying the MBS) can be unconstrained. That is, we study an optimization problem that jointly optimizes the traveling path, stopping points, charging schedule, and flow routing. For this problem, we propose a two-step solution. First, we study an idealized problem that assumes zero traveling time, and develop a provably near-optimal solution to this idealized problem. In the second step, we show how to develop a practical solution with non-zero traveling time and quantify the performance gap between this solution and the unknown optimal solution to the original problem. This dissertation offers the first systematic investigation on how WET (in particular, the MRC technology) can be exploited to address lifetime bottleneck of a WSN. It lays the foundation of exploring WET for WSNs and other energy-constrained wireless networks. On the mathematical side, we have developed or applied a number of powerful techniques such as piecewise linear approximation, RLT, time-space transformation, discretization, and logical point representation that may be applicable to address a broad class of optimization problems in wireless networks. We expect that this dissertation will open up new research directions on many interesting networking problems that can take advantage of the WET technology. / Ph. D.

Large-scale wireless sensor networks (WSNs) are highly vulnerable to attacks because they consist of numerous resource-constrained devices and communicate via wireless links. These vulnerabilities are exacerbated when WSNs have to operate unattended in a hostile environment, such as battlefields. In such an environment, an adversary poses a physical threat to all the sensor nodes. An adversary may capture any node, compromising critical security data including keys used for encryption and authentication. Consequently, it is necessary to provide security services to these networks to ensure their survival. We propose a novel, self-organizing key management scheme for large-scale and long-lived WSNs, called Survivable and Efficient Clustered Keying (SECK). SECK provides administrative services that ensures the survivability of the network. SECK is suitable for managing keys in a hierarchical WSN consisting of low-end sensor nodes clustered around more capable gateway nodes. Using cluster-based administrative keys, SECK provides five efficient security administration mechanisms: 1) clustering and key setup, 2) node addition, 3) key renewal, 4) recovery from multiple node captures, and 5) re-clustering. All of these mechanisms have been shown to localize the impact of attacks and considerably improve the efficiency of maintaining fresh session keys. Using simulation and analysis, we show that SECK is highly robust against node capture and key compromise while incurring low communication and storage overhead. / Master of Science

Wireless Sensor Networks (WSNs) are wireless networks that have recently drawn significant research attention since they offer unique benefits and versatility with respect to sensing, allowing low-power and low-cost rapid deployment for many applications that do not need human supervision. WSNs are self-created and self-organized by the collection of a large number of sensor nodes interconnected by multi-hop wireless paths. The sensor nodes are network embedded systems with Integrated Chips (ICs) to allow signal processing and micro-sensing. Each wireless sensor node is a micro-electro-mechanical device and can only be equipped with a limited power reserve. While energy consumption occurs in sensing, data processing and communications, care should be exercised to make the most of the expendable power source for the node. Though considerable research is being done in the area of energy saving techniques for WSNs, most of the proposed techniques have focused on energy awareness at different network layers in WSNs. Furthermore, most of the proposed techniques are based on protocols for mobile ad hoc networks that do not look into the possibility of a cross-layer design strategy that can exploit the unique features of WSNs. There still exists the need for a universal protocol that can be applied to such networks in general. In this thesis, we focus such a research on optimizing the energy consumption by suggesting a novel cross-layer architecture at the network/data-link layer for sensor networks. We have developed a scheme for better and improved energy efficiency in WSNs by combining the ideas of energy-efficient cluster formation and medium access together. Our cross-layer scheme provides good performance in terms of WSN-lifetime, scalability and minimizing network-wide energy consumption. The scheme is based on a collaborative approach supported by formation of dynamic clusters functioning with a traffic aware MAC (medium access control) scheme. Our MAC scheme incorporates a self-learning, traffic adaptive algorithm for varying traffic conditions inherent to the WSNs. The design methodology and results in this thesis aim at producing a reliable and scalable energy-aware sensing network, in spite of node failures, minimizing energy consumption at the same time. / Master of Science

With the increase in applications of wireless sensor networks, data extraction and visualisation have become a key issue to develop and operate these networks. Wireless sensor networks typically gather data at a discrete number of locations. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. The aim of this thesis is to develop a service for maximising information return from large scale wireless sensor networks. This aim will be achieved through the development of a distributed information extraction and visualisation service called the mapping service. In the distributed mapping service, groups of network nodes cooperate to produce local maps which are cached and merged at a sink node, producing a map of the global network. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisations. The proposed distributed mapping service utilises a blend of both inductive and deductive models to successfully map sense data and the universal physical principles. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of a sense modality. Furthermore, the proposed mapping service responds to changes in the environmental conditions that may impact the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a newdistributed self-adaptation algorithm, Virtual Congress Algorithm,which is based on the concept of virtual congress is proposed, with the goal of saving more power and generating more accurate data visualisation.

Recently, wireless sensor networks have become one of the most exciting areas for research and development. However, sensor nodes are battery operated, thus the sensor's ability to perform its assigned tasks is limited by its battery capacity; therefore, energy efficiency is considered to be a key issue in designing WSN applications. Clustering has emerged as a useful mechanism for trade-off between certain design goal conflicts; the network life time, and the amount of data obtained. However, different sources of energy waste still exist. Furthermore, in such dynamic environments, different data rate requirements emerge due to the current network status, thus adapting a response to the changing network is essential, rather than following the same principle during the network's lifespan. This thesis presents dynamic techniques to adapt to network changes, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Two approaches have been taken to decreasing the energy use. The first approach is to develop two dynamic round time controllers, called the minimum round time controller MIN-RC and the variable round time controller VAR-RC, whereas the second approach improves intra-cluster communication using a Co-Cluster head; both approaches show better energy utilisation compared to traditional protocols. A third approach has been to develop a general hybrid protocol H-RC that can adapt different applications requirements; it can also tolerate different data rate requirements for the same application during the system's lifetime.

O notável desenvolvimento da indústria eletrônica observado nos últimos tempos tem permitido aplicações de conjuntos integrados de sensores em ambientes sem fio, conhecidos por wireless sensor networks (WSN), que passam por sensoriamento de processos industriais, ambientes tóxicos, projetos militares de monitoração de variáveis de segurança, até observação de fenômenos físicos naturais. Uma das principais especificações de uma rede WSN, o consumo de energia afeta diretamente a capacidade e tempo de vida útil do sistema, pois, na maioria dos casos, seus módulos possuem baterias independentes e sua substituição nem sempre é tarefa simples. Motivado pela necessidade de oferecer robustez e economia de energia nas redes WSN, o protocolo difusão direcionada se baseia na centralização de dados e a identificação de seus módulos é feita por meio de pares valor-atributo. Sua estrutura permite a adição de componentes de software que podem atuar na análise e modificação dos dados recebidos com o objetivo de alterar o protocolo original. O objetivo principal deste trabalho é investigar um método para otimização do uso de energia disponível em redes WSN com intuito de prolongar seu tempo de vida útil. O metódo consiste em analisar os valores das energias atribuídas aos módulos componentes da rede por meio de incorporação de um algoritmo de rotas baseado em energia ao protocolo difusão direcionada. Comparações de desempenho da rede em relação ao seu tempo de vida e energia dos módulos são realizadas utilizando o simulador NS-2. As simulações feitas em diversos cenários indicaram melhoria de desempenho em relação ao protocolo difusão direcionada original. Os cenários onde o protocolo original foi alterado apresentaram um número maior de rotas descobertas e possibilitaram um aumento de pelo menos 22% no tempo de vida da rede, em relação ao protocolo original. / The notable development of electronic industry in the last years allows the implementation of sensor integrated circuits in wireless environments, known as wireless sensor networks (WSN), which leads to industrial process sensing, toxic environments, military security monitor projects and natural physical phenomenon. As one of the main specifications of a WSN network, the energy consumption directly affects the capacity and the system useful lifetime, since most of the time its modules have independent batteries and their substitution is not always a simple task. Motivated by the need of offering robustness and energy economy for WSN networks, the directed diffusion protocol is data-centric based and its modules identification is made by attribute-value pairs. The directed diffusion structure enables the addition of software components which can act on the analysis and modification of received data with the objective of changing the original protocol. The main objective of this work is to investigate a method for optimization of available energy on WSN networks with the intention of increasing its useful lifetime. The method consists on analyzing the energy values attributed to the component modules of the network by incorporating an energy-based routing algorithm to directed diffusion protocol. Performance comparisons of the network related to its lifetime and modules energy are developed using the NS-2 simulator. Simulations performed in several scenarios indicated a better performance in relation to the original directed diffusion protocol. The scenarios where the original protocol was changed had larger number of discovered routes and allowed a rising of at least 22% on network lifetime, in relation to the original protocol.

Nowadays, Opportunistic Routing (OR) is widely considered to be the most important paradigm for Multi-hop wireless networks (MWNs). It exploits the broadcast nature of wireless medium to propagate information from one point to another within the network. In OR scheme, when a node has new information to share, it rst needs to set its forwarding list which include the IDs and/or any relevant information to its best suited neighboring nodes. This operation is supported by the use of appropriate metrics. Then, it executes a coordination algorithm allowing transmission reliability and high throughput among the next-hop forwarders. In this paper, we provide a comprehensive guide to understand the characteristics and challenges faced in the area of opportunistic routing protocols in MWNs. Moreover, since the planet we live on is largely covered by water, OR protocols have gained much attention during the last decade in real-time aquatic applications, such as oil/chemical spill monitoring, ocean resource management, anti-submarine missions and so on. One of the major problems in Underwater Wireless Sensor Network (UWSNs) is determining an e cient and reliable routing methodology between the source node and the destination node. Therefore, designing e cient and robust routing protocols for UWSNs became an attractive topic for researchers. This paper seeks to address in detail the key factors of underwater sensor network. Furthermore, it calls into question 5 state-of-the-art routing protocols proposed for UWSN: The Depth-Based Routing protocol (DBR), the Energy-E cient Depth-Based Routing protocol (EEDBR), the Hydraulic-pressure-based anycast routing protocol (Hydrocast), the Geographic and opportunistic routing protocol with Depth Adjustment for mobile underwater sensor networks (GEDAR), and the Void- Aware Pressure Routing for underwater sensor networks (VAPR). Finally, it covers the performance of those protocol through the use of the R programming language.

Target tracking is one of the typical applications of wireless sensor networks: a large number of spatially deployed sensor nodes collaboratively sense, process and estimate the target state (e.g., position, velocity and heading). This thesis aimed to develop the collaborative information processing techniques that jointly address information processing and networking for the distributive estimation of target state in the highly dynamic and resources constrained wireless sensor networks. Taking into account the interplay between information processing and networking, this thesis proposed a collaborative information processing framework. The framework integrates the information processing which is responsible for the representation, fusion and processing of data and information with networking which caters for the formation of network, the delivery of information and the management of wireless channels. Within the proposed collaborative information processing framework, this thesis developed a suite of target tracking algorithms on the basis of the recursive Bayesian estimation method. For tracking a single target in wireless sensor networks, this thesis developed the sequential extended Kalman filter (S-EKF), the sequential unscented Kalman filter (S-UKF) and the Particle filter (PF). A novel extended Kalman filter and Particle filter hybrid algorithm, named as EKPF was also developed. The simulation results showed that the EKPF outperformed other three algorithms in terms of tracking accuracy and robustness. Moreover, to help evaluate the performance of the developed tracking algorithms, the posterior Cramer-Rao lower bound (PCRLB) which is the theoretical lower bound on the mean square error of the target state estimation was also computed. To tackle the measurement origin uncertainty in practical target tracking in wireless sensor networks, this thesis designed a Particle filter and probability density association filter (PDAF) hybrid algorithm, named as PF-PDAF for tracking a single target under the dual assumptions of clutter and missed detections. The PF-PDAF combines the advantages of PDAF algorithm in effectively solving the data association problem with the merits of PF that can accommodate the general non-Gaussian, nonlinear state space model. The PCRLB under measurement origin uncertainty was also derived and computed. For multiple target tracking in wireless sensor networks, this thesis designed a Particle filter and joint probabilistic data association filter (JPDAF) hybrid algorithm, named as PFJPDAF. The PF-JPDAF algorithm extends the traditional JPDAF to solve the general nonlinear non-Gaussian multiple targets tracking problems in wireless sensor networks. In the highly energy and communication bandwidth constrained wireless sensor networks, a critical consideration is that the information processing needs to be distributive. By adopting the hierarchical network architecture to achieve dynamic sensor nodes clustering and utilizing the Gaussian mixture model (GMM) to propagate estimation results amongst sensor clusters, this thesis developed the distributive PF, the distributive EKPF, the distributive PF-PDAF and the distributive PF-JPDAF tracking algorithms. Moreover, this thesis proposed a composite objective function incorporating both the information utility and the energy consumption measures to facilitate the sensing nodes selection in the distributive tracking algorithms. This composite objective function enables the distributive tracking algorithms to achieve the desirable tracking accuracy while still maintaining the lower energy consumption. / Thesis (Ph.D.) - University of Adelaide, School of Electrical and Electronic Engineering, 2008

This dissertation presents methods of extending the network lifetime of multi-hop wireless sensor networks (WSNs) through routing that uses cooperative transmission (CT), referred to as cooperative routing. CT can have a signal-to-noise ratio (SNR) advantage over non-CT schemes through cooperative diversity and simple aggregation of transmit power, and one of its abilities is to extend the communication range of a wireless device using this SNR advantage. In this research, we use the range-extension ability of CT as a tool to mitigate the energy-hole problem of multi-hop WSNs and extend the network lifetime. The main contributions of this research are (i) an analytical model for a cooperative routing protocol with a deployment method, (ii) cooperative routing protocols that can extend the network lifetime, and (iii) formulating the lifetime-optimization problem for cooperative routing. The analytical model developed in this research theoretically proves that, in a situation where non-CT routing cannot avoid the energy-hole problem, our CT method can solve the problem. PROTECT, a CT method based on the analytical model, provides a very simple way of doing cooperative routing and can improve the lifetime of non-CT networks significantly. REACT, a cooperative routing protocol that uses the energy information of nodes, overcomes some of the limitations of PROTECT and can be applied to any existing non-CT routing protocol to improve the network lifetime. Using REACT and analytical approaches, we also show that cooperative routing can be beneficial in multi-hop energy-harvesting WSNs. By formulating and solving the lifetime-optimization problem of cooperative routing, which requires a much more sophisticated formulation than that of non-CT routing, we explore the optimal lifetime bounds and behaviors of cooperative routing. Finally, we study and design online cooperative routing methods that can perform close to the optimal cooperative routing.

Wireless Underground Sensor Networks (WUSNs) are the networks of wireless sensors that operate below the ground surface. These sensors are either buried completely in soil medium, or placed within a bounded open underground space, such as underground mines and tunnels. WUSNs enable a wide variety of novel applications, including intelligent irrigation, underground structure monitoring, and border patrol and intruder detection. This thesis is concerned with establishing reliable and efficient communications in the network of wireless sensor nodes that are deployed in either soil medium or underground mines and tunnels. In particular, to realize WUSNs in soil medium, two types of signal propagation techniques including Electromagnetic (EM) waves and Magnetic Induction (MI) are explored. For EM wave-based WUSNs, the heterogeneous network architecture and dynamic connectivity are investigated based on a comprehensive channel model in soil medium. Then a spatio-temporal correlation-based data collection schemes is developed to reduce the sensor density while keeping high monitoring accuracy. For MI-based WUSNs, the MI channel is first analytically characterized. Then based on the MI channel model, the MI waveguide technique is developed in order to enlarge the underground transmission range. Finally, the optimal deployment algorithms for MI waveguides in WUSNs are analyzed to construct the WUSNs with high reliability and low costs. To realize WUSNs in underground mines and tunnels, a mode-based analytical channel model is first proposed to accurately characterize the signal propagation in both empty and obstructed mines and tunnels. Then the Multiple-Input and Multiple-Output (MIMO) system and cooperative communication system are optimized to establish reliable and efficient communications in underground mines and tunnels.