Target tracking using Wireless Sensor Networks (WSNs) has drawn lots of attentions after the recent advances of wireless technologies. Target tracking aims at locating one or several mobile objects and depicting their trajectories over time. The applications of Object Tracking Sensor Networks (OSTNs) include but not limited to environmental and wildlife monitoring, industrial sensing, intrusion detection, access control, traffic monitoring, patient monitoring in the health-related studies and location awareness in the battle eld. One of the most rewarding applications of target tracking is wildlife monitoring. Wildlife monitoring is used to protect the animals which are endangered to extinction. Road safety applications are another popular usage of wildlife monitoring using WSNs. In this thesis, the issues and challenges of energy-efficient wildlife monitoring and target tracking using WSNs are discussed. This study provides a survey of the proposed tracking algorithms and analyzes the advantages and disadvantages of these algorithms. Some of the tracking algorithms are proposed to increase the energy e ciency of the tracking algorithm and to prolong the network lifetime; while, other algorithms aim at improving the localization accuracy or decreasing the missing rate. Since improving the energy efficiency of the system provides more alive sensors over time to locate the target; it helps to decrease the missing rate as the network ages. Thus, this study proposes to adjust the sensing radius of the sensor nodes in real-time to decrease the sensing energy consumption and prolong the network lifetime. The proposed VAriable Radius Sensor Activation (VARSA) mechanism for target tracking using wireless sensor networks tackles the energy consumption issues due to resource constraints of the WSNs. VARSA reduces the radio covered area of each sensor node to only cover the Area of Interest (AoI) which is the location of the target in tracking applications. Thus, VARSA aims at decreasing the sensing energy consumption which leads to encreasing the network life time. In addition, VARSA decreases the missing rate over time as it provides more alive sensors to detect the target compared to previous activation algorithms as the network ages. VARSA is compared to PRediction-based Activation (PRA) and Periodic PRediction-based Activation (PPRA) algorithms which are two of the most promising algorithms proposed for sensor activation. The simulation results show that VARSA outperforms PRA and PPRA. VARSA prolongs the lifetime of the network and decreases the missing rate of the target over time.

In order to implement wireless sensing and monitoring services at large scale, Internet connection is highly desirable. Particularly, TCP is indispensable for end-to-end connection orientated communication. It is well known that low power and low rate IEEE802.15.4 based Wireless Sensor Networks (WSNs) are vulnerable to the interference from collocated Wireless Local Area Networks (WLAN) utilizing the same un-licensed 2.4GHz frequency band. Such coexistence interference seriously deteriorates the performance of TCP/IPv6 over WSN, resulting in packet losses, disconnections, reduced throughput and so on. This thesis focuses on experimental research on the performance evaluation and improvement of TCP/IPv6 over IEEE 802.15.4 based WSN. In this research, a versatile testbed has been developed and implemented, which consists of off-the-selves and custom built hardware, open source and in-house developed firmware and software. A periodical monitoring/sensing application that uses TCP to transmit data over WSN has been developed and used for performance evaluation when there is various Wi-Fi interference close by. Based on the observations and analysis of our experimental results, several important parameters that impact the TCP packet transmission performance have been identified. Performance improvement technique is proposed to effectively adjust these parameters so as to support periodic monitoring/sensing application with substantial better performance. Extensive experiments have been performed in the testbed to evaluate the performance of WSN packets transmission via TCP over WSN when subjected to different Wi-Fi interference.

Wireless sensor networks (WSNs) are an emerging area of technology that have applications across many domains. By adding a mobile platform to the WSN we can increase its capabilities. One such scenario involves a mobile platform relocating sensors to fill sensing holes that are the result of sensor failure. We examine this problem, known as robot-assisted sensor relocation (RASR), and propose our own, multi-objective version, that we call reliable robot-assisted sensor relocation. We solve this problem using a set of state-of-the-art evolutionary multi-objective optimization algorithms. Additionally, we examine the multi-robot model, which we christen reliable multiple robot-assisted sensor relocation (RMRASR). The works collected within define these problems as well as provide empirical insight into the performance of well-known algorithms using these problems as a test-bed.

The agricultural sector is an emerging application area for Wireless Sensor Networks (WSNs). This requires sensor nodes to be deployed in the outdoor environment so as to monitor pertinent natural features, such as soil condition or pest infestation. Limited energy supply and subsequent battery replacement are common issues for these agricultural sensor nodes. One possible solution is to use energy harvesting, where the ambient energy is extracted and converted into usable electrical form to energise the wireless sensors. The work presented in this thesis investigates the feasibility of using Radio Frequency (RF) energy harvesting for a specific application; that is powering a generic class of wireless ground-level, agricultural sensor networks operating in an outdoor environment. The investigation was primarily undertaken through a literature study of the subject. The first part of the thesis examines several energy harvesting/ wireless energy transfer techniques, which may be applicable to power the targeted agricultural WSN nodes. The key advantages and limitations of each technique are identified, and the rationale is being given for selecting far-field RF energy harvesting as the investigated technique. It is then followed by a theoretical-based system analysis, which seeks to identify all relevant design parameters, and to quantify their impact on the system performance. An RF link budget analysis was also included to examine the feasibility of using RF energy harvesting to power an exemplar WSN node - Zyrox2 Bait Station. The second part of the thesis focuses on the design of two energy harvesting antennas. The first design is an air-substrate-based folded shorted patch antenna (FSPA) with a solid ground plane, while the second design is a similar FSPA structure with four pairs of slot embedded into its ground plane. Both antennas were simulated, fabricated and tested inside an anechoic chamber, and in their actual operating environment - an outdoor field. In addition, a power harvester circuit, built using the commercially available off-the-shelf components, was tested in the laboratory using an RF signal generator source. The results from both the laboratory and field trial were analysed. The measurement techniques used were reviewed, along with some comments on how to improve them. Further work on the RF energy harvester, particularly on the improvement of the antenna design must be carried out before the feasibility and viable implementations for this application can be definitively ascertained.

This thesis, entitled Wireless Sensor Networks in Hostile RF Environments, was submitted to the The University of Manchester by Mr Dominic James Patrick Crutchley on 30th April 2012 for the degree Doctor of Philosophy (PhD). This thesis considers two different but related aspects of wireless communication in Wireless Sensor Networks (WSNs) operating in hostile environments. Using grain as an example of a hostile environment, the influence of hostile, attenuating media on Radio Frequency (RF) communications was considered. Further to this the implications of a hostile environment for protocol stacks were considered, and a cross-layer, cross-application framework was proposed to help future protocol designers address these issues. To achieve both these aims, the software for a bespoke WSN node was designed and implemented. The node was characterised to ensure a good understanding of its RF behaviour and practical experiments were then conducted in a small-scale grain silo to gain an understanding of attenuation and data communications within grain. Finally, a real world implementation of the proposed cross-layer, cross-application framework was produced and a small example cross-layer protocol was demonstrated running on the WSN node. It was shown that a WSN can be used to characterise communications within a hostile medium and also that data communications are achievable within grain. It was also shown that a small cross-layer, cross-application framework could ease the development of cross-layered protocols in WSN software.

To achieve greater performance in computing networks, a setup of critical computing aspects that ensures efficient network operation, needs to be implemented. One of these computing aspects is, Quality of Service (QoS). Its main functionality is to manage traffic queues by means of prioritizing sensitive network traffic. QoS capable networking allows efficient control of traffic especially for network critical data. However, to achieve this in Wireless Sensor Networks (WSN) is a serious challenge, since these technologies have a lot of computing limitations. It is even difficult to manage networking resources with ease in these types of technologies, due to their communication, processing and memory limitations. Even though this is the case with WSNs, they have been largely used in monitoring/detection systems, and by this proving their application importance. Realizing efficient network control requires intelligent methods of network management, especially for sensitive network data. Different network types implement diverse methods to control and administer network traffic as well as effectively manage network resources. As with WSNs, communication traffic and network resource control are mostly performed depending on independently employed mechanisms to deal with networking events occurring on different levels. It is therefore challenging to realize efficient network performance with guaranteed QoS in WSNs, given their computing limitations. Software defined networking (SDN) is advocated as a potential paradigm to improve and evolve WSNs in terms of capacity and application. A means to apply SDN strategies to these compute-limited WSNs, formulates software defined wireless sensor networks (SDWSN). In this work, a resource-aware OpenFlow-based Active Network Management (OF-ANM) QoS scheme that uses SDN strategies is proposed and implemented to apply QoS requirements for managing traffic congestion in WSNs. This scheme uses SDN programmability strategies to apply network QoS requirements and perform traffic load balancing to ensure congestion control in SDWSN. Our experimental results show that the developed scheme is able to provide congestion avoidance within the network. It also allows opportunities to implement flexible QoS requirements based on the system’s traffic state. Moreover, a QoS Path Selection and Resource-associating (Q-PSR) scheme for adaptive load balancing and intelligent resource control for optimal network performance is proposed and implemented. Our experimental results indicate better performance in terms of computation with load balancing and efficient resource alignment for different networking tasks when compared with other competing schemes. / Thesis (PhD)--University of Pretoria, 2019. / National Research Foundation / University of Pretoria / Electrical, Electronic and Computer Engineering / PhD / Unrestricted

Power management is an active area of research in wireless sensor networks (WSNs). Efficient power management is necessary because WSNs are battery-operated devices that can be deployed in mission-critical applications. From the communications perspective, one main approach to reduce energy is to maximize throughput so the data can be transmitted in a short amount of time. Frame fragmentation techniques aim to achieve higher throughput by reducing retransmissions. Using experiments on a WSN testbed, we show that frame fragmentation helps to reduce energy consumption. We then study and compare recent frame fragmentation schemes to find the most energy-efficient scheme. Our main contribution is to propose a new frame fragmentation scheme that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data with optimal transmit power and optimal frame structure based on environmental conditions. Green-Frag takes into consideration the channel conditions, interference patterns and level, as well as the distance between sender and receiver. The thesis discusses various design and implementation considerations for Green-Frag. Also, it shows empirical results of comparing Green-Frag with other frame fragmentation protocols in terms of energy efficiency. Green-Frag performance results shows that it is capable of choosing the best transmit according to the channel conditions. Subsequently, Green-Frag achieves the least energy consumption in all environmental conditions.

Security is a key challenge for any IIoT network and more so for constrained IWSN deployments. Novel methods are thus required to enhance security, taking into consideration the lossy and low power nature of the IWSN. The use of ICMP packets is proposed as a method to generate fingerprinting information for IWSN devices. The ICMP based method uses the round-trip time information in the ICMP header as a fingerprinting metric. The results showed that the effect of the physical layer can be averaged out of the measurement if enough samples are available. A linear relationship was found between hop count and round-trip time for a static network which can be used in the design phase of the IWSN network or alternatively as a method to fingerprint routing anomalies in real-time. The ICMP method was able to differentiate between devices from different vendors, but unable to fingerprint devices from the same vendor due to physical layer interference. The work shows that fingerprinting in an IWSN using the ICMP method is possible if the timing delta under investigation is an order of magnitude larger than the timing variation introduced by the physical layer while maintaining a reasonable signal-to-noise ratio. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2021. / Electrical, Electronic and Computer Engineering / MEng (Computer Engineering) / Unrestricted

The advancement of wireless technology has led to an increase in the employment of wireless sensor networks (WSNs). Traditionally, WSNs are powered by batteries. However, the high power consump- tion and the need to change the batteries regularly has made these networks costly to maintain. The nodes in the WSNs are increasingly strained as power consumption increases and the batteries are depleted faster. This has consequently decreased the overall lifetime of the WSNs. Although many energy-conserving techniques exist, for example energy-efficient medium access control and energy-efficient routing protocols, energy consumption remains one of the significant constraints in the development of WSNs. A natural solution to this constraint is harvesting energy from the environment. However, unlike conventional energy, energy harvested from the environment is random in nature, making it challenging to realise energy-harvesting transmission schemes. Although energy harvesting might be considered a solution to many problems, it brings about new challenges with regard to the usage and management of the energy harvested. Some of these challenges include uneven consumption of power in the network, resulting in dead nodes in some portion of the network and the batteries used in the network are being affected negatively by the energy usage; they may consequently sustain the nodes for long or short periods. To analyse the usage and consumption of energy, a number of techniques have been proposed, namely; information theory, game theory and queueing theory. By this time, the performance of the sensor nodes in WSNs has been analysed making use of a queueing-theoretic model for each sensor. The aforementioned model inadequately expresses the physical constraints, namely, the energy drawing process and the finite battery capacity. This research focuses on developing a model that captures the harvesting, accumulation and dissipation of energy, utilising queueing theory. A rechargeable battery with a finite storage capacity will be used. To ensure that the battery does not lose its capability to store charge after being recharged repeatedly, the leaky bucket model is proposed to check the network data flow as the harvested energy in the WSN is analysed. To capture real-world WSNs with energy harvesting in which there is energy leakage, the energy- harvesting sensor node performance is analysed with two assumptions: data transmission and energy leakage occurring and the token buffer being subjected to a threshold. The system had finite buffers for the data and energy. To make it possible to have some influence over the system performance measures a threshold is imposed on the token buffer. Four models are developed: a basic model, a basic model with leakage incorporated, a basic model with leakage and priority incorporated and a basic model with leakage, priority and threshold incorporated. The developed models are simulated and results for the performance measures are obtained. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2021. / BWMC, NRF / Electrical, Electronic and Computer Engineering / MEng (Computer Engineering) / Unrestricted

Wireless sensor networks enable inexpensive distributed monitoring systems that are the backbone of smart cities. In this dissertation, we are interested in wireless sensor networks for traffic monitoring and an emergency flood detection to improve the safety of future cities. To achieve real-time traffic monitoring and emergency flood detection, the system has to be continually operational. Accordingly, an energy source is needed to ensure energy availability at all times. The sun provides for the most inexpensive source of energy, and therefore the energy is provided here by a solar panel working in conjunction with a rechargeable battery. Unlike batteries, solar energy fluctuates spatially and temporally due to the panel orientation, seasonal variation and node location, particularly in cities where buildings cast shadows. Especially, it becomes scarce whenever floods are likely to occur, as the weather tends to be cloudy at such times when the emergency detection system is most needed. These considerations lead to the need for the optimization of the energy of the sensor network, to maximize its sensing performance. In this dissertation, we address the challenges associated with long term outdoor deployments along with providing some solutions to overcome part of these challenges. We then introduce the energy optimization problem, as a distributed greedy approach. Motivated by the flood sensing application, our objective is to maximize the energy margin in the solar powered network at the onset of the high rain event, to maximize the network lifetime. The decentralized scheme will achieve this by optimizing the energy over a time horizon T, taking into account the available and predicted energy over the entire routing path. Having a good energy forecasting scheme can significantly enhance the energy optimization in WSN. Thus, this dissertation proposes a new energy forecasting scheme that is compatible with the platform’s capabilities. This proposed prediction scheme was tested on real data and compared with state-of-theart forecasting schemes on on-node WSN platforms. Finally, to establish the relevance of the aforementioned schemes beyond theoretical formulations and simulations, all proposed protocols and schemes are subjected to hardware implementation.