Recent advances in VLSI technology, and wireless communication have enabled the development of tiny, low-cost sensor nodes that communicate over short distances. These sensor nodes, which consist of sensing, data processing, and wireless communication capabilities, suggest the idea of sensor networks based on collaborative effort of a large number of sensor nodes. Sensor networks hold the promise for numerous applications such as intrusion detection, weather monitoring, security and tactical surveillance, distributed computing, and disaster management. Several new protocols and algorithms have been proposed in the recent past in order to realize these applications. In this thesis, we consider the problem of routing in Wireless Sensor Networks (WSNs). Routing is a challenging problem in WSNs due to the inherent characteristics which distinguish these networks from the others. Several routing algorithms have been proposed for WSNs, each considering a specific network performance objective such as long network lifetime (ChangandTassiulas,2004), end-to-end delay guarantees (T.Heetal,2003), and data fusion (RazvanCristescuetal,2005) etc. In this thesis, we utilize the Potential-based Routing Paradigm to develop routing algorithms for different performance objectives of interest in WSNs. The basic idea behind the proposed approach is to assign a scalar called the potential to every sensor node in the network. Data is then forwarded to the neighbor with highest potential. Potentials cause the data to flow along certain paths. By defining potential fields appropriately, one can cause data to flow along preferred paths, so that the given performance objective is achieved. We have demonstrated the usefulness of this approach by considering three performance objectives, and defining potentials appropriately in each case. The performance objectives that we have considered are (i) maximizing the time to network partition, (ii) maximizing the packet delivery ratio, and (iii) Data fusion. In an operational sensor network, sensor nodes’ energy levels gradually deplete, leading eventually to network partition. A natural objective is to route packets in such a way that the time to network partition is maximized. We have developed a potential function for this objective. We analyzed simple network cases and used the insight to develop a potential function applicable to any network. Simulation results showed that considerable improvements in time to network partition can be obtained compared to popular approaches such as maximum lifetime routing, and shortest hop count routing. In the next step, we designed a potential function that leads to routes with high packet delivery ratios. We proposed a “channel-state aware” potential definition for a simple 2-relay network and performed a Markov-chain based analysis to obtain the packet delivery ratio. Considerable improvement was observed compared to a channel-state-oblivious policy. This motivated us to define a channel-state-dependent potential function for a general network. Simulation results showed that for a relatively slowly changing wireless network, our approach can provide up to 20% better performance than the commonly-used shortest-hop-count routing. Finally, we considered the problem of correlated data gathering in sensor networks. The routing approach followed in literature is to construct a spanning tree rooted at the sink. Every node in the tree aggregates its data with the data from its children in order to reduce the number of transmitted bits. Due to this fact, the total energy cost of the data collection task is a function of the underlying tree structure. Noting that potential based routing schemes also result in a tree structure, we present a potential definition that results in the minimum energy cost tree under some special conditions. Specifically, we consider a scenario in which sensor nodes’ measurements are quantized to K values. The task at the sink is to construct a histogram of measurements of all sensor nodes. Sensor nodes do not directly send their measurements to sink. Instead, they construct a temporary histogram using the data from its children and forward it to its parent node in the tree. We present a potential definition that results in the minimum energy cost tree under some conditions on sensor nodes’ measurements. We include both the transmission energy cost as well as the energy cost associated with the aggregation process.

Wireless Sensor Networks (WSNs) are composed of a large number of battery-powered sensor nodes that have the ability to sense the physical environment, compute the obtained information and communicate using the radio interfaces. Because sensor nodes are generally deployed on a large and wild area, they are powered by embedded battery. And it is difficult to change or recharge the battery, thus to reduce the energy consumption when sensors and protocols are designed is very important and can extend the lifetime of WSNs. So sensor nodes transmit packets with a lower transmission power (e.g. OdBm). With this transmission power, a packet can only be transmitted dozens of meters away. Therefore, when a sensor detects an event, a packet is sent in a multi-hop, ad-hoc manner (without fixed infrastructure and each sensor is able to relay the packet) to the sink (specific node which gathers information and reacts to the network situation). In this thesis, we first give an elaborate state of the art of WSNs. Then the impacts of duty-cycle and unreliable links or the performances of routing layer are analyzed. Based on the analytical results, we then propose three new simple yet effective methods to construct virtual coordinates under unreliable links in WSNs. By further taking the duty-cycle and real-time constraints into consideration we propose two cross-layer forwarding protocols which can have a greater delivery ratio and satisfy the deadline requirements. In order to have protocols for the WSNs that have dynamic topology, we then propose a robust forwarding protocol which can adapt its parameters when the topology changes. At last, we conclude this thesis and give some perspectives.

Wireless Sensor Networks (WSN) may consist of hundreds or even thousands of nodes and could be used for a multitude of applications such as warfare intelligence or to monitor the environment. A typical WSN node has a limited and usually irreplaceable power source and the efficient use of the available power is of utmost importance to ensure maximum lifetime of each WSN application. Each of the nodes needs to transmit and communicate sensed data to an aggregation point for use by higher layer systems. Data and message transmission among nodes collectively consume the largest amount of the energy available in a WSN. The network routing protocols ensure that every message reaches the destination and has a direct impact on the amount of transmissions to deliver a messages successfully. To this end the transmission protocol within the WSN should be scalable, adaptable and optimized to consume the least possible amount of energy to suite different network architectures and application domains. This dissertation proposes a Mobile Tolerant Hybrid Energy Efficient Routing Protocol (MT-HEER), where hybrid refers to the inclusion of both flat and hierarchical routing architectures as proposed by Page in the Hybrid Energy Efficient Routing Protocol (HEER). HEER was previously developed at the University of Pretoria and forms the starting point of this research. The inclusion of mobile nodes in the WSN deployment proves to be detrimental to protocol performance in terms of energy efficiency and message delivery. This negative impact is attributable to assuming that all nodes in the network are statically located. In an attempt to adapt to topological changes caused by mobile nodes, too much energy could be consumed by following traditional network failure algorithms. MT-HEER introduces a mechanism to pro-actively track and utilise mobile nodes as part of the routing strategy. The protocol is designed with the following in mind: computational simplicity, reliability of message delivery, energy efficiency and most importantly mobility awareness. Messages are propagated through the network along a single path while performing data aggregation along the same route. MT-HEER relies on at least 40% of the nodes in the network being static to perform dynamic route maintenance in an effort to mitigate the risks of topological changes due to mobile nodes. Simulation results have shown that MT-HEER performs as expected by preserving energy within acceptable limits, while considering the additional energy overhead introduced by dynamic route maintenance. Mobile node tolerance is evident in the protocol's ability to provide a constant successful message delivery ratio at the sink node with the introduction and increase in the number of mobile nodes. MT-HEER succeeds in providing tolerance to mobile nodes within a WSN while operating within acceptable energy conservation limits. AFRIKAANS : Koordlose Sensor Netwerke mag bestaan uit honderde of selfs duisende nodes en kan gebruik word vir 'n legio van toepassings soos oorlogs intellegensie of om die omgewing te monitor. 'n Tipiese node in so 'n netwerk het 'n beperkte en soms onvervangbare energie bron. Die effektiewe gebruik van die beskikbare energie is dus van uiterste belang om te verseker dat die maksimum leeftyd vir 'n koordlose sensor network behaal kan word. Elkeen van die nodes in the network moet die waargeneemde data aanstuur oor die netwerk na 'n versamelings punt vir latere gebruik deur applikasie vlak stelsels. Informasie en boodskap transmissie tussen die nodes is wel een van die aktiwiteite wat die meeste energie verbruik in the netwerk. Die roeterings protokol verseker dat die boodskappe die eindbestemming behaal en het 'n direkte impak op die hoeveelheid transmissies wat kan plaas vind om dit te bewerkstellig. Die roeterings protokol moet dus skaleerbaar, aanpasbaar en verfyn word om die minste moontlike energie te verbruik in verskillende toepassings velde. Hierdie verhandeling stel 'n Bewegings Tolerante Hybriede Netwerk Roeterings Protokol vir Koordlose Sensor Netwerke (“MT-HEER”) voor. In hierdie konteks verwys hybried na die samesmelting van beide plat en hierargiese roeterings beginsels soos voor gestel deur Page in Hybriede Netwerk Roeterings Protokol (“HEER”). HEER was ontwikkel by die Universiteit van Pretoria en vorm die begin punt van hierdie navorsing. Die insluiting van bewegende nodes in 'n Koordlose Sensor Netwerk toon 'n negatiewe tendens in terme van energie effektiwiteit en suksesvolle boodskap aflewerings by die eindbestemming. Die grootste rede vir hierdie negatiewe tendens is die aanname deur gepubliseerde werke dat alle nodes in die netwerk staties is. Te veel energie sal vermors word indien tradisionele fout korregerende meganismes gevolg word om aan te pas by die bewegende nodes. MT-HEER stel 'n meganisme voor om die bewegende nodes te gebruik as deel van die roetering strategie en gevolglik ook hierdie nodes te volg soos hulle beweeg deur die netwerk. Die protokol is ontwikkel met die volgende doelstellings: rekenkundig eenvoudigheid, betroubare boodskap aflewering, energie effektiwiteit en bewustheid van bewegende nodes. Boodskappe word langs 'n enkele pad gestuur deur die netwerk terwyl boodskap samevoeging bewerkstellig word om die eind bestemming te bereik. MT-HEER vereis wel dat ten minste 40% van die netwerk nodes staties bly om die dienamiese roeterings instandhouding te bewerkstellig. Simulasie toetse en resultate het bewys dat MT-HEER optree soos verwag in gevalle waar daar bewegende nodes deel uit maak van die netwerk. Energie bewaring is binne verwagte parameters terwyl die addisionele energie verbruik binne rekening gebring word om te sorg vir bewegende nodes. Die protokol se toleransie teen bewegende nodes word ten toon gestel deur die vermoë van die protokol om konstant 'n hoë suksesvolle bookskap aflewerings verhouding te handhaaf. MT-HEER behaal die uitgesette doel om 'n toleransie teen bewegende nodes beskikbaar te stel, terwyl die protokol steeds funksioneer binne verwagte energie besparings limiete. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted

Die Dissertation erforscht die Unsicherheit, Sensitivität und Grenzen großskaliger Erosionsmodelle. Die Modellierung basiert auf der allgemeinen Bodenabtragsgleichung (ABAG), Sedimenteintragsverhältnissen (SDR) und europäischen Daten. Für mehrere Regionen Europas wird die Bedeutung der Unsicherheit topographischer Modellparameter, ABAG-Faktoren und kritischer Schwebstofffrachten für die Anwendbarkeit empirischer Modelle zur Beschreibung von Sedimentfrachten und SDR von Flusseinzugsgebieten untersucht. Der Vergleich alternativer Modellparameter sowie Kalibrierungs- und Validierungsdaten zeigt, dass schon grundlegende Modellentscheidungen mit großen Unsicherheiten behaftet sind. Zur Vermeidung falscher Modellvorhersagen sind kalibrierte Modelle genau zu dokumentieren. Auch wenn die geschickte Wahl nicht-topographischer Algorithmen die Modellgüte regionaler Anwendungen verbessern kann, so gibt es nicht die generell beste Lösung. Die Ergebnisse zeigen auch, dass SDR-Modelle stets mit Sedimentfrachten und SDR kalibriert und evaluiert werden sollten. Mit diesem Ansatz werden eine neue europäische Bodenabtragskarte und ein verbessertes SDR-Modell für Einzugsgebiete nördlich der Alpen und in Südosteuropa abgeleitet. In anderen Regionen Europas ist das SDR-Modell bedingt nutzbar. Die Studien zur jährlichen Variabilität der Bodenerosion zeigen, dass jahreszeitlich gewichtete Niederschlagsdaten geeigneter als ungewichtete sind. Trotz zufriedenstellender Modellergebnisse überwinden weder sorgfältige Algorithmenwahl noch Modellverbesserungen die Grenzen europaweiter SDR-Modelle. Diese bestehen aus der Diskrepanz zwischen modellierten Bodenabtrags- und maßgeblich zur beobachteten bzw. kritischen Sedimentfracht beitragenden Prozessen sowie der außergewöhnlich hohen Sedimentmobilisierung durch Hochwässer. Die Integration von nicht von der ABAG beschriebenen Prozessen und von Starkregentagen sowie die Disaggregation kritischer Frachten sollte daher weiter erforscht werden. / This dissertation thesis addresses the uncertainty, sensitivity and limitations of large-scale erosion models. The modelling framework consists of the universal soil loss equation (USLE), sediment delivery ratios (SDR) and European data. For several European regions, the relevance of the uncertainty in topographic model parameters, USLE factors and critical yields of suspended solids for the applicability of empirical models to predict sediment yields and SDR of river catchments is systematically evaluated. The comparison of alternative model parameters as well as calibration and validation data shows that even basic modelling decisions are associated with great uncertainties. Consequently, calibrated models have to be well-documented to avoid misapplication. Although careful choices of non-topographic algorithms can also be helpful to improve the model quality in regional applications, there is no definitive universal solution. The results also show that SDR models should always be calibrated and evaluated against sediment yields and SDR. With this approach, a new European soil loss map and an improved SDR model for river catchments north of the Alps and in Southeast Europe are derived. For other parts of Europe, the SDR model is of limited use. The studies on the annual variability of soil erosion reveal that seasonally weighted rainfall data is more appropriate than unweighted data. Despite satisfactory model results, neither the careful algorithm choice nor model improvements overcome the limitations of pan-European SDR models. These limitations are related to the mismatch of modelled soil loss processes and the relevant processes contributing to the observed or critical sediment load as well as the extraordinary sediment mobilisation during floods. Therefore, further research on integrating non-USLE processes and heavy-rainfall data as well as on disaggregating critical yields is needed.

The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.

<div>A growing global population and improved standard of living in developing countries have resulted in an unprecedented increase in energy demand over the past several decades. While renewable energy sources are increasing, a huge portion of energy is still converted into useful work using heat engines. The combustion process in diesel and petrol engines releases carbon dioxide and other greenhouse gases as an unwanted side-effect of the energy conversion process. By improving the efficiency of internal combustion engines, more chemical energy stored in petroleum resources can be realized as useful work and, therefore, reduce global emissions of greenhouse gases. This research focused on improving the thermal efficiency of opposed-piston engines, which, unlike traditional reciprocating engines, do not use a cylinder head. The cylinder head is a major source of heat loss in reciprocating engines. Therefore, the opposed-piston engine has the potential to improve overall engine efficiency relative to inline or V-configuration engines.</div><div><br></div>The objective of this research project was to further improve the design of opposed-piston engines by using computational fluid dynamics (CFD) modeling to optimize the engine geometry. The CFD method investigated the effect of intake port geometry and exhaust piston lead angle on the scavenging process and in-cylinder turbulence. After the CFD data was analyzed, scavenging efficiency was found insensitive to transfer port geometry and exhaust piston lead angle with a maximum change of 0.61%. Trapping efficiency was altered exclusively by exhaust piston lead angle and changed from 18% to 26% as the lead angle was increased. The in-cylinder turbulence parameters of the engine (normalized swirl circulation, normalized tumble circulation, and normalized TKE) experienced more complex relationships. All turbulence parameters were sensitive to changing transfer port geometry and exhaust piston lead angle. Some examples of trends seen during the analysis include: an increase in normalized swirl circulation from 0.01 to 4.45 due to changes in swirl angle, a change in normalized tumble circulation from -28.52 to 21.11 as swirl angle increased, and an increase in normalized tumble circulation from 14.20 to 33.68 as exhaust piston lead angle was increased. Based on the present work, an optimum configuration was identified for a swirl angle of 15°, a tilt angle of 10°, and an exhaust piston lead angle of 20°. Future work includes expanding the numerical model’s domain to support a complete cylinder-port configuration, adding combustion products to the diffusivity equation in the UDF, and running additional test cases to describe the entire input space for the sensitivity analysis.<br>