Unprecedented traffic growth is expected in future wireless networks and new technologies will be needed to satisfy demand. Optical wireless (OW) communication offers vast unused spectrum and high area spectral efficiency. In this work, optical cells are envisioned as supplementary access points within heterogeneous RF/OW networks. These networks opportunistically offload traffic to optical cells while utilizing the RF cell for highly mobile devices and devices that lack a reliable OW connection. Visible light communication (VLC) is considered as a potential OW technology due to the increasing adoption of solid state lighting for indoor illumination. Results of this work focus on a full system view of RF/OW HetNets with three primary areas of analysis. First, the need for network densication beyond current RF small cell implementations is evaluated. A media independent model is developed and results are presented that provide motivation for the adoption of hyper dense small cells as complementary components within multi-tier networks. Next, the relationships between RF and OW constraints and link characterization parameters are evaluated in order to define methods for fair comparison when user-centric channel selection criteria are used. RF and OW noise and interference characterization techniques are compared and common OW characterization models are demonstrated to show errors in excess of 100x when dominant interferers are present. Finally, dynamic characteristics of hyper dense OW networks are investigated in order to optimize traffic distribution from a network-centric perspective. A Kalman Filter model is presented to predict device motion for improved channel selection and a novel OW range expansion technique is presented that dynamically alters coverage regions of OW cells by 50%. In addition to analytical results, the dissertation describes two tools that have been created for evaluation of RF/OW HetNets. A communication and lighting simulation toolkit has been developed for modeling and evaluation of environments with VLC-enabled luminaires. The toolkit enhances an iterative site based impulse response simulator model to utilize GPU acceleration and achieves 10x speedup over the previous model. A software defined testbed for OW has also been proposed and applied. The testbed implements a VLC link and a heterogeneous RF/VLC connection that demonstrates the RF/OW HetNet concept as proof of concept.

Software-defined Networking (SDN) is an emerging trend in communication networks that facilitates decoupling the control and data plane of multilayer switches. A logically centralized controller hosted on a server configures the forwarding tables (flow tables) of switches in order to route the various data flows.  To implement SDN, OpenFlow technology has been adopted by packet switching vendors as it provides increased flexibility for the control and management of a packet switched domain. OpenFlow technology provides flow based switching that is controlled by a network management control application running in an OpenFlow controller. In this thesis work we investigate how an OpenFlow Controller communicates with a legacy network via the OSPF routing protocol, how the size of the OpenFlow network effects the resources (memory and CPU) of a legacy router to whom the controller communicates. Also we examine bandwidth utilization of the link (between the OpenFlow network and legacy router). The main goal of this thesis is to find methods to reduce the consumption of resources of a legacy router. This study shows that the size of OpenFlow network directly affects the usage of the link’s bandwidth, and the memory and CPU usage of a legacy router. Aggregated information from the OpenFlow controller which is sent towards the legacy router can reduce the utilization of these resources. Finally we proposed several algorithms and design models that can be implemented for route aggregation in Software-defined Networks.  Implementation of the solutions suggested in this thesis will allow automatic route aggregation in SDN. ISPs deploying SDN architecture could benefit from the proposed design models and route aggregation solution. / Software-definierade nätverk (SDN) är en framväxande trend i kommunikationsnät som underlättar frikoppling kontroll och uppgifter plan flerskiktade switchar. Ett logiskt centraliserad styrenhet på en server konfigurerar vidarebefordran tabeller (flödestabeller) av växlar för att dirigera de olika dataflöden. För att genomföra SDN har OpenFlow teknik har antagits av paketförmedlande leverantörer eftersom det ger ökad flexibilitet för kontroll och förvaltning av en påslagen paket domän. OpenFlow teknik ger flöde baserad omkoppling som styrs av ett nätverk ledningens kontroll som körs i en OpenFlow controller. I detta examensarbete undersöker vi hur en OpenFlow Controller kommunicerar med ett äldre nätverk via OSPF routing protokoll, hur storleken på OpenFlow nätverkseffekter de resurser (minne och CPU) av en äldre router till vilken styrenheten kommunicerar.  Också vi undersöker bandbreddsutnyttjandet av sambandet (mellan OpenFlow nätverket och äldre router). Det huvudsakliga målet med detta examensarbete är att hitta metoder för att minska konsumtionen av resurser från en äldre router. Denna studie visar att storleken på OpenFlow nätverk direkt påverkar användningen av länkens bandbredd och minne och CPU-användning av en äldre router. Samlad information från OpenFlow styrenhet som sändes mot äldre router kan minska utnyttjandet av dessa resurser. Slutligen föreslog vi flera algoritmer och modeller konstruktion som kan genomföras för route aggregation i Software Defined-nätverk. Genomförandet av de lösningar som föreslås i denna avhandling kommer att möjliggöra automatisk route aggregation i SDN. Internetleverantörer distribuerar SDN arkitektur kunde dra nytta av den föreslagna utformningen modeller och route aggregation lösning.

Our main objective is to design Dimensional Analysis (DA) algorithms for the multidimensional dialect PyLucid of Lucid, the equational data flow language. The significance is that the DA is indispensable for an efficient implementation of multidimensional Lucid and should aid the implementation of other data flow systems, such as Google’s TensorFlow. Data flow is a form of computation in which components of multidimensional datasets (MDDs) travel on communication lines in a network of processing stations. Each processing station incrementally transforms its input MDDs to its output, another (possibly very different) MDD. MDDs are very common in Health Information Systems and data science in general. An important concept is that of relevant dimension. A dimension is relevant if the coordinate of that dimension is required to extract a value. It is very important that in calculating with MDDs we avoid non-relevant dimensions, otherwise we duplicate entries (say, in a cache) and waste time and space. Suppose, for example, that we are measuring rainfall in a region. Each individual measurement (say, of an hour’s worth of rain) is determined by location (one dimension), day, (a second dimension) and time of day (a third dimension). All three dimensions are a priori relevant. Now suppose we want the total rainfall for each day. In this MDD (call it N) the relevant dimensions are location and day, but time of day is no longer relevant and must be removed. Normally this is done manually. However, can this process be automated? We answer this question affirmatively by devising and testing algorithms that produce useful and reliable approximations (specifically, upper bounds) for the dimensionalities of the variables in a program. By dimensionality we mean the set of relevant dimensions. For example, if M is the MDD of raw rain measurements, its dimensionality is {location, day, hour}, and that of N is {location, day}. Note that the dimensionality is more than just the rank, which is simply the number of dimensions. Previously, there’s extensive research on dataflow itself, which we summarize. However, an exhaustive literature search uncovered no relevant previous DA work other than that of the GLU (Granular Lucid) project in the 90s. Unfortunately the GLU project was funded privately and remains proprietary – not even the author has access to it. Our methodology is that we proceeded incrementally, solving increasingly difficult instances of DA corresponding to increasingly sophisticated language features. We solved the case of one dimension (time), two dimensions (time and space), and multiple dimensions. We also solved the difficult problem (which the GLU team never solved) of determining the dimensionality of programs that include user defined functions, including recursively defined functions. We do this by adapting the PyLucid interpreter (to produce the DAM interpreter) to evaluating the entire program over the (finite) domain of dimensionalities. As a result, the experimentally validated algorithms in our dissertation can produce useful upper bounds for the dimensionalities of the variables in multidimensional PyLucid programs. That also includes those with user-defined functions / Graduate

Inspection methods for satellites post-launch are currently expensive and/or dangerous. To address this, BYU, in conjunction with NASA, is designing a series of small satellites called CubeSATs. These small satellites are designed to be launched from a satellite and to visually inspect the launching body. The current satellite revision passively tumbles through space and is appropriately named the passive inspection cube satellite (PICS). The next revision actively maintains translation and rotation relative to the launching satellite and is named the translation, rotation inspection cube satellite (TRICS). One of the necessary sensors aboard this next revision is the means to detect distance. This work explores the feasibility of using a software defined radio as a small, low-cost front end for a ranging radar to fulfill this need. For this work, the LimeSDR-Mini is selected due to its low-cost, small form factor, full duplex operation, and open-source hardware/software. Additionally, due to the the channel characteristics of space, the linear frequency modulated continuous-wave (LFMCW) radar is selected as the radar architecture due to its ranging capabilities and simplicity. The LFMCW radar theory and simulation are presented. Two programming methods for the LimeSDR-Mini are considered: GNU Radio Companion and the pyLMS7002Soapy API. GNU Radio Companion is used for initial exploration of the LimeSDR-Mini and confirms its data streaming (RX and TX) and full duplex capabilities. The pyLMS7002Soapy API demonstrates further refined control over the LimeSDR-Mini while providing platform independence and deployability. This work concludes that the LimeSDR-Mini is capable of acting as the front end for a ranging radar aboard a small satellite provided the pyLMS7002Soapy API is used for configuration and control. GNU Radio Companion is not recommended as a programming platform for the LimeSDR-Mini and the pyLMS7002Soapy API requires further research to fine tune the SDR's performance.

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The notion of the networked society is more than ever true nowadays. The Internet has a big impact on our daily lives. Network operators provide the underlying infrastructure and continuously deploy services in order to meet customer demands. The amount of data transported through operator networks is also increasing with the introduction of new high band width services and over the network content. That being said, operators, most often deploy or operate networks to meet these demands without any regard to energy-efficiency. As the price of electricity continues to grow,  tends to become a problem with serious implications. To solve this problem a trend towards more energy efficient networks has emerged. In this thesis, we investigate a way to facilitate the introduction of new energy efficiency paradigms for fixed networks. Towards this end, we investigate the energy efficiency schemes proposed up to now and select one that we believe is more realistic to deploy. Furthermore, we specify the inputs required for the selected “green” routing approach. Moreover, we study existing and new protocols that can provide basic network monitoring functionality that enables the acquirement of these inputs. In the end, a Software Defined Networking (SDN) approach is proposed to facilitate the development of energy-efficient aware networks. The details of a basic SDN monitoring application are presented from an abstract architectural point of view and three designs stemming from this basic architecture are discussed. The three designs are namely All_Flow, First_Switch and Port_FlowRemoved. The first two were implemented as steps towards understanding the full capabilities of performing monitoring in SDN enabled networks and provided useful input towards realizing the third one as a proof of concept. Their usage and faults are discussed as they can provide useful insight for possible future implementations. The Port_FlowRemoved is the design and implementation that is suggested as providing the most fitting results for the monitoring purpose at hand. This purpose is to retrieve the identified inputs for the selected “green” networking approach. The differentiation factor among the three designs is how they collect the required inputs from the network. A fast-prototype is created as a proof of concept in order to validate the proposed architecture and thus empower the validity of the idea.

Several heterogeneous, intelligent and distributed devices can be connected to interact with one another over the internet in what is known as the internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for increasing the production output of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). More so, the benefits of IoT technology can be particularly exploited across the maritime industry in what is termed the internet of maritime things (IoMT) where sensors and actuator devices are implanted on marine equipment in order to foster the communication efficacy of nautical radio networks. Marine explorations may suffer from unwanted situations such as transactional delays, environmental degradation, insecurity, seaport congestions, accidents and collisions etc, which could arise from severe environmental conditions. As a result, there is a need to develop proper communication techniques that will improve the overall quality of service (QoS) and quality of experience (QoE) of marine users. To address these, the merits of contemporaneous technologies such as ubiquitous computing, software-defined networking (SDN) and network functions virtualization (NFV) in addition to salubrious communication techniques including emergent configurations (EC), channel estimation (CE) and communication routing protocols etc, can be utilized for sustaining optimal operation of pelagic networks. Emergent configuration (EC) is a technology that can be adapted into maritime radio networks to support the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this thesis, a survey on the concept of IoT is presented in addition to a review of IIoT systems. The applications of ubiquitous computing and SDN technology are employed to design a newfangled network architecture which is specifically propounded for enhancing the throughput of oil and gas production in the maritime ecosystem. The components of this architecture work in collaboration with one another by attempting to manage and control the exploration process of deep ocean activities especially during emergencies involving anthropogenic oil and gas spillages. Several heterogeneous, intelligent and distributed devices can be connected to interact with one another over the internet in what is known as the internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for increasing the production output of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). More so, the benefits of IoT technology can be particularly exploited across the maritime industry in what is termed the internet of maritime things (IoMT) where sensors and actuator devices are implanted on marine equipment in order to foster the communication efficacy of nautical radio networks. Marine explorations may suffer from unwanted situations such as transactional delays, environmental degradation, insecurity, seaport congestions, accidents and collisions etc, which could arise from severe environmental conditions. As a result, there is a need to develop proper communication techniques that will improve the overall quality of service (QoS) and quality of experience (QoE) of marine users. To address these, the merits of contemporaneous technologies such as ubiquitous computing, software-defined networking (SDN) and network functions virtualization (NFV) in addition to salubrious communication techniques including emergent configurations (EC), channel estimation (CE) and communication routing protocols etc, can be utilized for sustaining optimal operation of pelagic networks. Emergent configuration (EC) is a technology that can be adapted into maritime radio networks to support the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this thesis, a survey on the concept of IoT is presented in addition to a review of IIoT systems. The applications of ubiquitous computing and SDN technology are employed to design a newfangled network architecture which is specifically propounded for enhancing the throughput of oil and gas production in the maritime ecosystem. The components of this architecture work in collaboration with one another by attempting to manage and control the exploration process of deep ocean activities especially during emergencies involving anthropogenic oil and gas spillages. On the other hand, CE is a utilitarian communication technique that can be exploited during maritime exploration processes which offer additional reinforcement to the capacities of the nautical radio network. This technique enables the receivers of deep-sea networks to efficiently approximate the channel impulse response (CIR) of the wireless communication channel so that the effects of the communication channel on the transmitting aggregated cluster head information can be proficiently understood and predicted for useful decision-making procedures. Two CE schemes named inter-symbol interference/ average noise reduction (ISI/ANR) and reweighted error-reducing (RER) are designed in this study for estimating maritime channels for supporting the communication performances of nautical radio networks in both severe and light-fading environmental conditions. In the proposed RER method, the Manhattan distance of the CIR of an orthodox adaptive estimator is taken, which is subsequently normalised by a stability constant ɛ whose responsibility is for correcting any potential numerical system instability that may arise during the updating stages of the estimation process. To decrease the received signal error, a log-sum penalty function is eventually multiplied by an adjustable leakage (ɛ ) ̈that provides additional stability to the oscillating channel behaviour. The performance of the proposed RER method is further strengthened and made resilient against channel effects by the introduction of a reweighting attractor that further contracts the mean square error of this proposed estimator. In the ISI/ANR technique, the effects of possible ISI that may arise from maritime transmissions is considered and transformed using a low-pass filter that is incorporated for eliminating the effects of channel noise possible effects of multipath propagation. The RER scheme offered superior CE performances in comparison to other customary techniques such as the adaptive recursive least squares and normalised least mean square method in addition to conventional linear approaches such as least squares, linear minimum mean square error and maximum-likelihood estimation method. The proposed ISI/ANR technique offered an improved MSE performance in comparison to all considered linear methods. Finally, from this study, we were able to establish that accurate CE methods can improve the QoS and QoE of nautical radio networks in terms of network data rate and system outage probability. / Thesis (PhD (Computer Engineering))--University of Pretoria, 2021. / University of Pretoria Doctoral research grant, South African National Research Foundation/Research and Innovation Support and Advancement (NRF/RISA) research grant. Center for Connected Intelligence, Advanced Sensor Networks research group, University of Pretoria. / Electrical, Electronic and Computer Engineering / PhD (Computer Engineering) / Unrestricted

In the last decade, data networks have shifted from the static deployment of resources to a dynamic approach. With the help of Software Defined Networks (SDN) and Network Function Visualization (NFV), information and data about the network can be collected. Also, deployment and allocation of resources can be delegated to a central controller. In this thesis we investigate the power of SDN and how central management of resources can help produce better and efficient data networks. It begins with an introduction to SDN and its capabilities. The added benefits of SDN over traditional network frameworks and topics that SDN contributed most to. We show the power of collecting data using SDN and how it enables different approaches to accomplish the needed task. This was facilitated by the programmability and the separation of the control and data planes. We tackle the simple task of measuring the delay between two communicating devices in the network. The results show that SDN is capable of providing a rich infrastructure to build future networks. Also, it illustrates that using SDN to measure the delay between devices in the network can give accurate results. The differences between the tested techniques is shown and evaluated. After collecting the data from the network, the next step is getting an insight on that data. Next we used collected network bandwidth data to predict future bandwidth usage. We used various prediction models to establish prediction intervals. We created a state of the art metric that evaluates and compares the performance of each model. We show that the network bandwidth is highly predictable and that dynamic allocation of network bandwidth is attainable. The next logical step is to act upon those insight which is investigated next. We establish the same prediction models investigated but instead of prediction intervals we establish upper quantiles. Prediction is done on data center resources data set. The results show that using quantile prediction can give guarantees on resources usage boundaries which implies a guarantee on service level agreements. Allocating just the needed resources, produce a more efficient data center and in turn cuts a lot of the needed energy. Our estimate show that upto 56% of power can be saved without violating the service level agreement. / Graduate

In recent years, a new generation of architecture has emerged in the world of computer networks, known as software-defined networking (SDN), that aims to improve and remove the limitations of traditional networks. Although SDN provides viable benefits, it has faced many security threats and vulnerability-related issues. To solve security issues in the SDN, one of the most vital solutions is employing an intrusion detection system (IDS). Merging IDS into the SDN network remains efficient due to the unique features of SDN, such as high manageability, flexibility, and programmability. In this paper, we propose a new approach as a kangaroo-based intrusion detection system (KIDS), which is an SDN-based architecture for attack detection and malicious behaviors in the data plane. Designing a zone-based architecture in the KIDS assists us in achieving a distributed architecture which is scalable in both area and anomaly detection. In the KIDS architecture, the IDS module supplies the flow-based and packet-based intrusion detection components based on monitoring packet parser and Flow tables of the SDN switches. In the proposed approach, the IDS uses consecutive jumps like a kangaroo for announcing the attacks both to the SDN controller and other IDSs, contributing to improved scalability and efficiency. The evaluation of the proposed approach shows an enhanced performance against that of peer approaches in detecting malicious packets.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis firstly surveys and summarizes the state-of-the-art studies from two research areas in Software De fined Networking (SDN) architecture: (i) control plane scalability and (ii) Quality of Service (QoS)-related problems. It also outlines the potential challenges and open problems that need to be addressed further for more scalable SDN control planes and better and complete QoS abilities in SDN networks. The thesis secondly presents a hierarchical SDN design along with an inter-AS QoS-guaranteed routing approach. This design addresses the scalability problems of control plane and privacy concerns of inter-AS QoS routing philosophies in SDN. After exploring the roots of control plane scalability problems in SDN, the thesis then proposes a metric to quantitatively evaluate the control plane scalability in SDN. Later, the thesis presents a general framework for economic analysis of network architectures and designs. To this end, the thesis defines and utilizes two metrics, Unit Service Cost Scalability and Cost-to-Service, to evaluate how SDN architecture performs compared to MPLS architecture in terms of unit cost for a service and cost of introducing a new service along with giving mathematical models to calculate Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) of a network. Moreover, the thesis studies the problem of optimal final pricing for services by proposing an optimal pricing scheme for a service request with QoS in SDN environment while aiming to maximize benefits of both service providers and customers. Finally, the thesis investigates how programmable network architectures, i.e. SDN, affect the network economics compared to traditional network architectures, i.e. MPLS, in case of failures along with exploring the economic impact of failures in different SDN control plane models.