Wireless Sensor Networks (WSNs) are typically used to monitor specific phenomena and gather the data to a gateway node, where the data is further processed. WSNs nodes have limited power resources, which require developing power efficient systems. Additionally, reaching the nodes after a deployment to correct any design flaws is very challenging due the distributed nature of the nodes. The current development of WSNs occurs at the coding layer, which prevent the design from going through a typical software design process. Designing and analyzing the software modules of a WSN system at a higher abstraction layer than at the coding level will enable the designer of a WSN to fix any design errors and improve the system for power consumption at an early design stage, before the actual deployment of the network. This thesis presents multiple Unified Modeling Language (UML) design patterns that enable the designer to capture the structure and the behavior of the design of a WSN at higher abstraction layers. The UML models are developed based on these design patterns that are capable of early validation of the functional requirements and the power consumption of the system hardware resources by leveraging animation and instrumentation of the UML diagrams. To support the analysis of power consumption of the communication components of a WSN node, the Avrora network simulator was integrated with the UML design environment such that designer is able to analyze the power consumption analysis of the communication process at the UML layer. The UML and the Avrora simulation integration is achieved through developing a code generator that produces the necessary configuration for Avrora simulator and through parsing the simulator results. The methodology presented in this thesis is evaluated by demonstrating the power analysis of a typical collector system.

The purpose of this research is to reduce maintenance resources and improve Escravos–Gas–to–Liquids plant availability (EGTL) in Escravos, Nigeria using wireless condition monitoring. Secondary to the above is to justify the use of this technology over other conventional condition monitoring methods in petrochemical plants with specific reference to cost, reliability and security of the system. Wireless and continuous condition monitoring provides the means to evaluate current conditions of equipment and detect abnormalities. It allows for corrective measures to be taken to prevent upcoming failures. Continuous monitoring and event recording provides information on the energized equipment's response to normal and emergency conditions. Wireless/remote monitoring helps to coordinate equipment specifications and ratings, determine the real limits of the monitored equipment and optimize facility operations. Bentley N, (2005). Using wireless techniques eliminate any need for special cables and wires with lower installation costs if compared to other types of condition monitoring systems. In addition to this, wireless condition monitoring works well under difficult conditions in strategically important locations. The Escravos gas–to–liquid plant in Nigeria, located in a remote and offshore area where accommodation and space for offices is a factor for monitoring plant conditions in every office, is a typical example. Wireless technology for condition monitoring of energized equipment is applicable to both standalone and remote systems. In the research work of Meyer and Brambley (2002), they characterized the current problem with regards to cost effectiveness and availability of wireless condition monitoring. Maintenance of rotating equipment provides probability estimates of the total impact of the problem, cost implication of plant equipment maintenance and describes a generic system in which these developing technologies are used to provide real–time wireless/remote condition monitoring for rotating main air compressor (MAC) units and their components as a case study. Costs with today’s technology are provided and future costs are estimated, showing that benefits will greatly exceed costs in many cases, particularly if low–cost wireless monitoring is used. With management trends such as “re–engineering” and “downsizing” of the available workforce, wireless condition–monitoring of critical machines has been given more importance as a way to ensure quality production with fewer personnel. Wireless condition–monitoring using inexpensive wireless communication technology frees up existing plant maintenance personnel work on machines that are signaling problems and focusing the maintenance efforts away from attempting to work on a large population of machines to only those machines requiring immediate attention. Lloyd and Buddy (200) suggested that Point–to–point wireless data transmission systems, an excellent example of recent technological advances in communication systems, are now practical and cost–effective for industrial use. While both complex infrastructures and complex protocols are required for cellular communications, non– cellular communication systems, such as the point–to–point wireless data transmission system example, require no elaborate infrastructure. Limited research was done on the immediate benefits of implementing wireless condition monitoring systems in plants. All papers on the subject have been drawn up by manufacturers of such equipment. This research will thus also deliver a "third–party" perspective on the effectiveness of such devices, justifying their impact on data gathering security, cost and reliability. / Thesis (M.Ing. (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2012.

The main focus of the work presented in this thesis concerns the development and improvement of Wireless Sensor Networks (WSNs) as well as Wireless Body Area Networks (WBANs). WSN consist of interlinked, wireless devices (nodes) capable of relaying data wirelessly between the nodes. The applications of WSNs are very broad and cover both wireless fitness monitoring systems such as pulse watches or wireless temperature monitoring of buildings, among others. The topics investigated in the work presented within this thesis covers antenna design, wireless propagation environment evaluation and modeling, adaptive antenna control and wireless nodes system design and evaluation. In order to provide an end-user suitable solution for wireless nodes the devices require both small form factor and good performance in order to be competitive on the marked and thus the main part of this thesis focuses on techniques developed and data collected to help achieve these goals.  Several different prototype systems have been developed which have been used to measure data by the Swedish Defence Research Agency (FOI), GKN Aerospace Sweden AB, the Swedish Transport Administration. The system developed with GKN Aerospace was used to do real-time test measurements inside a running RM12 jet engine and required a substantial amount of measurements, environmental modeling and system validation in order to properly design a wireless system suitable for the harsh and fast fading environment inside a jet engine. For FOI improvements were made on a wearable wireless body area network initially developed during the authors master thesis work. Refinements included work on new generation wireless nodes, antenna packaging and node-supported diversity techniques. Work and papers regarding the design of different types of antennas suitable for wireless nodes are presented. The primary constraints on the presented antennas are the limited electrical size. The types of antennas developed include electrically small helix antennas manufactured both on stretchable substrates consisting of a PDMS substrate with Galinstan as the liquid metal conductors, screen printed silver ink for helix antennas and conformal dual patch antennas for wireless sensor nodes. Other standard type antennas are included on the wireless sensors as well.

Wireless sensor networks (WSN) increasingly permeate modern societies nowadays. But in spite of their plethora of successful applications, WSN are often unable to surmount many operational challenges that unexpectedly arise during their lifetime. Fortunately, robotic agents can now assist a WSN in various ways. This thesis illustrates how mobile robots which are able to carry a limited number of sensors can help the network react to sensor faults, either during or after its deployment in the monitoring region. Two scenarios are envisioned. In the first one, carrier robots surround a point of interest with multiple sensor layers (focused coverage formation). We put forward the first known algorithm of its kind in literature. It is energy-efficient, fault-reactive and aware of the bounded robot cargo capacity. The second one is that of replacing damaged sensing units with spare, functional ones (coverage repair), which gives rise to the formulation of two novel combinatorial optimization problems. Three nature-inspired metaheuristic approaches that run at a centralized location are proposed. They are able to find good-quality solutions in a short time. Two frameworks for the identification of the damaged nodes are considered. The first one leans upon diagnosable systems, i.e. existing distributed detection models in which individual units perform tests upon each other. Two swarm intelligence algorithms are designed to quickly and reliably spot faulty sensors in this context. The second one is an evolving risk management framework for WSNs that is entirely formulated in this thesis.

Wireless Sensor Networks (WSNs) have enticed a strong attention in the research community due to the broad range of applications and services they support. WSNs are composed of intelligent sensor nodes that have the capabilities to monitor different types of environmental phenomena or critical activities. Sensor nodes operate under stringent requirements of scarce power resources, limited storage capacities, limited processing capabilities, and hostile environmental surroundings. However, conserving sensor nodes’ power resources is the top priority requirement in the design of a WSN as it has a direct impact on its lifetime. The IEEE 802.15.4 standard defines a set of specifications for both the PHY layer and the MAC sub-layer that abide by the distinguished requirements of WSNs. The standard’s MAC protocol employs an intelligent backoff algorithm, called the Binary Exponent Backoff (BEB), that minimizes the drainage of power in these networks. In this thesis we present an in-depth study of the IEEE 802.15.4 MAC protocol to highlight both its strong and weak aspects. We show that we have enticing opportunities to improve the performance of this protocol in the context of WSNs. We propose three new backoff algorithms, namely, the Standby-BEB (SB-BEB), the Adaptive Backoff Algorithm (ABA), and the Priority-Based BEB (PB-BEB), to replace the standard BEB. The main contribution of the thesis is that it develops a new design concept that drives the design of efficient backoff algorithms for the IEEE 802.15.4-based WSNs. The concept dictates that controlling the algorithms parameters probabilistically has a direct impact on enhancing the backoff algorithm’s performance. We provide detailed discrete-time Markov-based models (for AB-BEB and ABA) and extensive simulation studies (for the three algorithms) to prove the superiority of our new algorithms over the standard BEB.

This dissertation presents algorithms for achieving communication in the presence of adversarial attacks in large, decentralized, resource-constrained networks. We consider abstract single-hop communication settings where a set of senders 𝙎 wishes to directly communicate with a set of receivers 𝙍. These results are then extended to provide resource-efficient, multi-hop communication in wireless sensor networks (WSNs), where energy is critically scarce, and peer-to-peer (P2P) networks, where bandwidth and computational power are limited. Our algorithms are provably correct in the face of attacks by a computationally bounded adversary who seeks to disrupt communication between correct participants. The first major result in this dissertation addresses a general scenario involving single-hop communication in a time-slotted network where a single sender in 𝙎 wishes to transmit a message 𝘮 to a single receiver in 𝙍. The two players share a communication channel; however, there exists an adversary who aims to prevent the transmission of 𝘮 by periodically blocking this channel. There are costs to send, receive or block 𝘮 on the channel, and we ask: How much do the two players need to spend relative to the adversary in order to guarantee transmission of the message? This problem abstracts many types of conflict in information networks, and the associated costs represent an expenditure of network resources. We show that it is significantly more costly for the adversary to block 𝘮 than for the two players to achieve communication. Specifically, if the cost to send, receive and block 𝘮 in a slot are fixed constants, and the adversary spends a total of 𝘉 slots to try to block the message, then both the sender and receiver must be active in only O(𝘉ᵠ⁻¹ + 1) slots in expectation to transmit 𝘮, where φ = (1+ √5)/2 is the golden ratio. Surprisingly, this result holds even if (1) the value of 𝘉 is unknown to either player; (2) the adversary knows the algorithms of both players, but not their random bits; and (3) the adversary is able to launch attacks using total knowledge of past actions of both players. Finally, these results are applied to two concrete problems. First, we consider jamming attacks in WSNs and address the fundamental task of propagating 𝘮 from a single device to all others in a WSN in the presence of faults; this is the problem of reliable broadcast. Second, we examine how our algorithms can mitigate application-level distributed denial-of-service attacks in wired client-server scenarios. The second major result deals with a single-hop communication problem where now 𝙎 consists of multiple senders and there is still a single receiver who wishes to obtain a message 𝘮. However, many of the senders (strictly less than half) can be faulty, failing to send 𝘮 or sending incorrect messages. While the majority of the senders possess 𝘮, rather than listening to all of 𝙎 and majority filtering on the received data, we desire an algorithm that allows the single receiver to decide on 𝘮 in a more efficient manner. To investigate this scenario, we define and devise algorithms for a new data streaming problem called the Bad Santa problem which models the selection dilemma faced by the receiver. With our results for the Bad Santa problem, we consider the problem of energy-efficient reliable broadcast. All previous results on reliable broadcast require devices to spend significant time in the energy-expensive receiving state which is a critical problem in WSNs where devices are typically battery powered. In a popular WSN model, we give a reliable broadcast protocol that achieves optimal fault tolerance (i.e., tolerates the maximum number of faults in this WSN model) and improves over previous results by achieving an expected quadratic decrease in the cost to each device. For the case where the number of faults is within a (1-∊)-factor of the optimal fault tolerance, for any constant ∊>0, we give a reliable broadcast protocol that improves further by achieving an expected (roughly) exponential decrease in the cost to each device. The third and final major result of this dissertation addresses single-hop communication where 𝙎 and 𝙍 both consist of multiple peers that need to communicate in an attack-resistant P2P network. There are several analytical results on P2P networks that can tolerate an adversary who controls a large number of peers and uses them to disrupt network functionality. Unfortunately, in such systems, operations such as data retrieval and message sending incur significant communication costs. Here, we employ cryptographic techniques to define two protocols both of which are more efficient than existing solutions. For a network of 𝘯 peers, our first protocol is deterministic with O(log²𝘯) message complexity and our second protocol is randomized with expected O(log 𝘯) message complexity; both improve over all previous results. The hidden constants and setup costs for our protocols are small and no trusted third party is required. Finally, we present an analysis showing that our protocols are practical for deployment under significant churn and adversarial behaviour.

Due to their economic potential and widespread application areas, wireless sensor networks have emerged as an active research topic during the last five years. One of the fundamental challenges in wireless sensor network research is the provision of sufficient coverage while maintaining energy efficiency and longevity under sensor mobility. The purpose of this thesis is to observe the coverage and energy consumption dynamics of a mobile wireless sensor network in a hierarchical architecture. To achieve this goal iv we implemented a simulation environment with flat and hierarchical topologies. Defining performance metrics and network parameters we performed simulations in MATLAB test-bed. With the help of results obtained from simulations and performance metrics&rsquo / relation to networks parameters we investigated the effect of hierarchical organization on mobile wireless sensor network coverage.

Mobile sensor networks have been shown to be a powerful tool for enabling a number of activities that require recording of environmental parameters at various spatial and temporal distributions. These mobile sensor networks could be implemented using a team of robots, usually called robotic sensor networks. This type of sensor network involves the coordinated control of multiple robots to achieve specific measurements separated by varied distances. In most formation measurement applications, initialization involves identifying a number of interesting sites to which mobility platforms, instrumented with a variety of sensors, are tasked. This process of determining which instrumented robot should be tasked to which location can be viewed as solving the task allocation problem. Unfortunately, a centralized approach does not fit in this type of application due to the fault tolerance requirements. Moreover, as the size of the network grows, limitations in bandwidth severely limits the possibility of conveying and using global information. As such, the utilization of decentralized techniques for forming new sensor topologies and configurations is a highly desired quality of robotic sensor networks. In this thesis, several distributed task allocation algorithms will be explained and compared in different scenarios. They are based on a market approach since our interest is not only to obtain a feasible solution, but also an efficient one. Also, an analysis of the efficiency of those algorithms using probabilistic techniques will be explained. Finally, the task allocation algorithms will be implemented on a real system consisted of a team of six robots and integrated in a complete robotic system that considers obstacle avoidance and path planning. The results will be validated in both simulations and real experiments.

Providing efficient data transport is one of the uppermost objectives in the design of wireless sensor networks (WSNs) since the primary role for each sensor is to report the sensed data to the data sink(s). This thesis focuses on designing efficient data transport schemes for WSNs in the dimensions of energy consumption and time respectively. The developed schemes can be directly applied in a number of applications such as intrusion detection, target tracking, environment monitoring, etc., and can be further extended to underwater acoustic sensor networks and unmanned aerial vehicles (UAVs) networks. With the development of WSN technologies, new challenging research problems such as real-time streaming data gathering and intelligent data communication are emerging. This thesis provides useful foundation for designing next-generation data transport schemes for WSNs. Energy is the most important resource in WSNs because sensor nodes are commonly powered by small batteries, and energy is directly related to the lifetime of nodes and the network. In this thesis, energy-efficient data transport schemes are designed for two major types of WSNs: event-driven sensor networks and time-driven sensor networks. A novel on-line routing scheme called EBGR (Energy-efficient Beaconless Geographic Routing) is designed for event-driven sensor networks characterized by dynamic network topology. The main advantage of EBGR is that it can provide energy-efficient sensor-to-sink routing without any prior neighborhood knowledge. Moreover, the total energy consumption for sensor-to-sink data delivery under EBGR has an upper bound. Time-driven sensor networks, in which all sensors periodically report the sensed data to the sink(s), have been widely used for environment monitoring applications. Unbalanced energy consumption is an inherent problem in time-driven sensor networks. An efficient data gathering scheme, called EBDG (Energy-Balanced Data Gathering), is designed to balance energy consumption for the goal of maximizing network lifetime. Combing all advantages of corona-based network division,mixed-routing and data aggregation, EBDG can prolong network lifetime by an order of magnitude compared with conventional schemes. Time-efficient data transport is another critical issue in WSNs since the data generated by the sensor nodes may become outdated after a certain time interval. This thesis focuses on the problem of providing real-time data gathering in time-driven sensor networks. A novel data gathering scheme based on random access is proposed with the objective to minimize the average duration for completing one round of data gathering. Fully localized solutions have been designed for both linear networks and tree networks. A simple data gathering protocol called RADG (Random Access Data Gathering) is designed. Simulation results show that RADG outperforms CSMA based schemes when the size of the data packets is small. / Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2009

Success of Wireless Sensor Networks (WSN) largely depends on whether the deployed network can provide desired area coverage with acceptable network lifetime. In hostile or harsh environments such as enemy territories in battlefields, fire or chemical spills, it is impossible to deploy the sensor nodes in a predeter- mined regular topology to guarantee adequate coverage. Random deployment is thus more practical and feasible for large target areas. On the other hand, random deployment of sensors is highly susceptible to the occurrence of coverage holes in the target area. A potential solution for enhancing the existing coverage achieved by random deployments involves the use of mobility capable sensors that would help fill the coverage holes. This thesis seeks to address the problem of determining the current coverage achieved by the non-deterministic deployment of static sensor nodes and subsequently enhancing the coverage using mobile sensors. The main contributions of this dissertation are the design and evaluation of MAPC (Mobility Assisted Probabilistic Coverage), a distributed protocol for ensuring area coverage in hybrid wireless sensor networks. The primary contribution is a pragmatic approach to sensor coverage and maintenance that we hope would lower the technical barriers to its field deployment. Most of the assumptions made in the MAPC protocol are realistic and implementable in real-life applications e.g., practical boundary estimation, coverage calculations based on a realistic sensing model, and use of movement triggering thresholds based on real radio characteristics etc. The MAPC is a comprehensive three phase protocol. In the first phase, the static sensors calculate the area coverage using the Probabilistic Coverage Algorithm (PCA). This is a deviation from the idealistic assumption used in the binary detection model, wherein a sensor can sense accurately within a well defined (usually circular) region. Static sensors execute the PCA algorithm, in a distributed way, to identify any holes in the coverage. In the second phase, MAPC scheme moves the mobile nodes in an optimal manner to fill these uncovered locations. For different types of initial deployments, the proposed movement algorithms consume only 30-40% of the energy consumed by the basic virtual force algorithm. In addition, this thesis addresses the problem of coverage loss due to damaged and energy depleted nodes. The problem has been formulated as an Integer Linear Program and implementable heuristics are developed that perform close to optimal solutions. By replacing in-operational nodes in phase three, MAPC scheme ensures the continuous operation of the WSN. Experiments with real mote hardware were conducted to validate the boundary and coverage estimation part of the MAPC protocol. Extensive discrete event simulations (using NS2) were also performed for the complete MAPC protocol and the results demonstrate that MAPC can enhance and maintain the area coverage by efficiently moving mobile sensor nodes to strategic positions in the uncovered area.