Computer networks can be classified into two broad categories: wired networks and wireless networks, according to the hardware and software technologies used to interconnect the individual devices. Wired interconnection networks are hardware fabrics supporting communications between individual processors in highperformance computing systems (e.g., multi-computer systems and cluster systems). On the other hand, due to the rapid development of wireless technologies, wireless networks have emerged and become an indispensable part for people¿s lives. The integration of different wireless technologies is an effective approach to accommodate the increasing demand of the users to communicate with each other and access the Internet. This thesis aims to investigate the performance of wired interconnection networks and integrated wireless networks under the realistic working conditions. Traffic patterns have a significant impact on network performance. A number of recent measurement studies have convincingly demonstrated that the traffic generated by many real-world applications in communication networks exhibits bursty arrival nature and the message destinations are non-uniformly distributed. Analytical models for the performance evaluation of wired interconnection networks and integrated wireless networks have been widely reported. However, most of these models are developed under the simplified assumption of non-bursty Poisson process with uniformly distributed message destinations. To fill this gap, this thesis first presents an analytical model to investigate the performance of wired interconnection networks in multi-computer systems. Secondly, the analytical models for wired interconnection networks in multi-cluster systems are developed. Finally, this thesis proposes analytical models to evaluate the end-to-end delay and throughput of integrated wireless local area networks and wireless mesh networks. These models are derived when the networks are subject to bursty traffic with non-uniformly distributed message destinations which can capture the burstiness of real-world network traffic in the both temporal domain and spatial domain. Extensive simulation experiments are conducted to validate the accuracy of the analytical models. The models are then used as practical and cost-effective tools to investigate the performance of heterogeneous wired or wireless networks under the traffic patterns exhibited by real-world applications.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have / Ministry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in London

no / Multimedia applications in wireless networks are usually categorized into various classes according to their traffic patterns and differentiated Quality-of-Service (QoS) requirements. The traffic of heterogeneous multimedia applications often exhibits the Long-Range Dependent (LRD) and Short-Range Dependent (SRD) properties, respectively. The integrated scheduling scheme that combines Priority Queuing (PQ) and Generalized Processor Sharing (GPS) within a hierarchical structure, referred to as PQ-GPS, has been identified as an efficient mechanism for QoS differentiation in wireless networks and attracted significant research efforts. However, due to the high complexity and interdependent relationship among traffic flows, modelling of the integrated scheduling scheme poses great challenges. To address this challenging and important research problem, we develop an original analytical model for PQ-GPS systems under heterogeneous LRD and SRD traffic. A cost-effective flow decomposition approach is proposed to equivalently divide the integrated scheduling system into a group of Single-Server Single-Queue (SSSQ) systems. The expressions for calculating the queue length distribution and loss probability of individual traffic flows are further derived. After validating its accuracy, the developed model is adopted as an efficient performance tool to investigate the important issues of resource allocation and call admission control in the integrated scheduling system under QoS constraints.

No / An analytic framework is devised, based on the principle of maximum entropy (ME), for the performance modelling and evaluation of a wireless GSM/GPRS cell supporting bursty multiple class traffic of voice calls and data packets under complete partitioning (CPS), partial sharing (PSS) and aggregate sharing (ASS) traffic handling schemes. Three distinct open queueing network models (QNMS) under CPS, PSS and ASS, respectively, are described, subject to external compound Poisson traffic processes and generalised exponential (GE) transmission times under a repetitive service blocking mechanism and a complete buffer sharing management rule. Each QNM generally consists of three building block stations, namely a loss system with GSM/GPRS traffic and a system of access and transfer finite capacity queues in tandem dealing with GPRS traffic under head-of-line and discriminatory processor sharing scheduling disciplines, respectively. The analytic methodology is illustrated by focusing on the performance study of the GE-type tandem queueing system for GPRS under a CPS. An ME product-form approximation is characterised leading into a decomposition of the tandem system into individual queues and closed-form ME expressions for state and blocking probabilities are presented. Typical numerical examples are included to validate the ME solutions against simulation and study the effect of external GPRS bursty traffic upon the performance of the cell. Moreover, an overview of recent extensions of the work towards the analysis of a GE-type multiple server finite capacity queue with preemptive resume priorities and its implications towards the performance modelling and evaluation of GSM/GPRS cells with PSS and ASS are included. / ,

Based on literature, a theoretical model was developed for viable performance consisting of eight constructs whilst the trust model of Martins (2000) was used to measure four organisational trust constructs. Exploratory factor analysis was used to extract the constructs, and structural equation modelling was employed to validate the models against the data. An empirical model for viable performance resulted in a solution with seven constructs and organisational trust with five constructs. The two empirical models were unified into a model of viable performance and trust resulting in a measurement model where all 12 constructs were shown. Significant levels of internal consistency were measured. The resulting measurement model was tested for group differences, and no significant differences were found, indicating that the assessment can be used across different groups. It was concluded that the aim to construct and test an integrated and comprehensive theoretical framework of viable performance and trust was achieved and the resulting Viable Performances and Trust Indicator (VPTI) was validated as an assessment to be used across groups. Organisations can thus use the framework and VPTI assessment tool with confidence to assess performance and trust across different biographical groups. Future researchers can build on this exploratory study to refine the scales and apply the measurement model within the wider context of South Africa or as a globally accepted model. / IndustriaI and Organisational Psychology / D. Litt. et Phil. (IndustriaI and Organisational Psychology)

Cloud computing is an exciting concept that propels the development of technologies, the creation and expansion of businesses and the rapid prototyping of new ideas. Utilizing the advantages the cloud offers to their fullest potential is not a simple task and thus often users struggle with the technological aspects, lose revenue or do not attempt to benefit from this idea at all. In this dissertation, we identify the lack of standards for performance descriptions as well as the steep learning curve to get familiar with the cloud, which is further amplified by the abundance of available services, as the most prevalent issues that individuals and companies encounter. We further show the relevance of solving these issues by outlining the expected impact, which includes decreased time and financial detriments for individuals and companies as well as a negative effect on the environment. To solve the identified problems we propose the development of a cloud broker with three key components that utilize a performance oriented resource and application model to 1) compare arbitrary resources and applications in a fair manner based on general information, collected with standard benchmark tools 2) select the optimal infrastructure for any application by estimating its resource consumption and execution time and 3) automatically create and manage the selected infrastructure as well as the application deployment. Our contributions to this proposal include the development and test of prototypical proof-of-concept implementations for the three components, the design of the underlying resource and application performance model as well as the selection of appropriate, generic benchmark solutions, which we deployed on two major public clouds using our prototypes. In an extensive objective-based evaluation we assess that we contributed towards solving all the major issues that we identified to increase the usability and efficiency of cloud computing by enabling a better comprehension of resource and application performance in cloud environments and by reducing the necessary time and effort to deploy arbitrary applications in the cloud. We conclude by interpreting the evaluation results and providing an outlook towards future work.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform / Die Dissertation beschäftigt sich mit der effizienten Nutzung von Cloud Ressourcen zur Beschleunigung der Entwicklung neuer Technologien und Geschäftsmodellen sowie des Rapid Prototypings neuer Ideen. Auf Grund der Komplexität von Cloud Plattformen, stellt die Nutzung derer oft eine große Hürde, speziell für kleine und mittlere Unternehmen dar, weshalb oft Ressourcen verschwendet werden, Prozesse mehr Zeit in Anspruch nehmen als nötig oder erst gar kein Versuch unternommen wird, diese Technologie zu nutzen. In der Arbeit werden dazu drei Kernprobleme identifiziert und thematisiert. Dies sind Lücken in Bezug auf Standards zur Beschreibung der Performance von Cloud Ressourcen, die Fülle an existierenden Cloud Diensten, sowie die steile Lernkurze bei der Nutzung dieser Dienste. Zur Lösung der identifizierten Probleme, wird in der Arbeit die Entwicklung einer Cloud Broker Anwendung mit drei Kernkomponenten vorgeschlagen, die ein Performanz-orientiertes Ressourcen- und Anwendungsmodell verwenden, welches es ermöglicht: 1) beliebige Ressourcen und Anwendungen unterschiedlichster Anbieter mit der Hilfe von frei verfügbaren und standardisierten Benchmark Tools zu vergleichen, 2) die passende Infrastruktur für jede auszuführende Anwendung durch Schätzung des Ressourcenbedarfs und der Dauer der Ausführung auszuwählen und 3) die gewählte Infrastruktur automatisch in der Cloud erzeugt und die Anwendung selbstständig ausführt. Im Rahmen der Dissertation wurden dazu alle drei Kernkomponenten prototypisch implementiert, das zugrundeliegende Ressourcen und Anwendungsmodell designt, sowie geeignete Benchmark Lösungen ausgewählt und umfangreiche Benchmarks auf zwei großen, öffentlichen Cloud Plattformen mit Hilfe der entwickelten Prototypen durchgeführt. In einer umfassenden zielorientierten Evaluation, wird der Beitrag zur Lösung der im Vorfeld identifizierten Probleme bewertet und festgestellt, dass mit den entwickelten Komponenten sowohl die Nutzbarkeit als auch Effizienz von Cloud-Computing insgesamt erhöht werden kann. Dies wird ermöglicht durch ein besseres Verständnis der Ressourcen und Anwendungsperformanz, sowie durch Reduzierung der notwendigen Zeit und des Aufwands für eine Anwendungsausführung in der Cloud. Im Vortrag wird abschließend noch ein Ausblick auf weiterführende Arbeiten gegeben.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform

Virtualisation is one of the underlying technologies that led to the success of cloud computing platforms (CCPs). The technology, along with other features such as multitenancy allows delivering of computing resources in the form of service through efficient sharing of physical resources. As these resources are provided through virtualisation, a robust agreement is outlined for both the quantity and quality-of-service (QoS) in a service level agreement (SLA) documents. QoS is one of the essential components of SLA, where performance is one of its primary aspects. As the technology is progressively maturing and receiving massive acceptance, researchers from industry and academia continue to carry out novel theoretical and practical studies of various essential aspects of CCPs with significant levels of success. This thesis starts with the assessment of the current level of knowledge in the literature of cloud computing in general and CCPs in particular. In this context, a substantive literature review was carried out focusing on performance modelling, testing, analysis and evaluation of Infrastructure as a Service (IaaS), methodologies. To this end, a systematic mapping study (SMSs) of the literature was conducted. SMS guided the choice and direction of this research. The SMS was followed by the development of a novel open queueing network model (QNM) at equilibrium for the performance modelling and analysis of an OpenStack IaaS CCP. Moreover, it was assumed that an external arrival pattern is Poisson while the queueing stations provided exponentially distributed service times. Based on Jackson’s theorem, the model was exactly decomposed into individual M/M/c (c ≥ 1) stations. Each of these queueing stations was analysed in isolation, and closed-form expressions for key performance metrics, such as mean response time, throughput, server (resource) utilisation as well as bottleneck device were determined. Moreover, the research was extended with a proposed open QNM with a bursty external arrival pattern represented by a Compound Poisson Process (CPP) with geometrically distributed batches, or equivalently, variable Generalised Exponential (GE) interarrival and service times. Each queueing station had c (c ≥ 1) GE-type servers. Based on a generic maximum entropy (ME) product form approximation, the proposed open GE-type QNM was decomposed into individual GE/GE/c queueing stations with GE-type interarrival and service times. The evaluation of the performance metrics and bottleneck analysis of the QNM were determined, which provided vital insights for the capacity planning of existing CCP architectures as well as the design and development of new ones. The results also revealed, due to a significant impact on the burstiness of interarrival and service time processes, resulted in worst-case performance bounds scenarios, as appropriate. Finally, an investigation was carried out into modelling and analysis of performance and security trade-offs for a CCP architecture, based on a proposed generalised stochastic Petri net (GSPN) model with security-detection control model (SDCM). In this context, ‘optimal’ combined performance and security metrics were defined with both M-type or GE-type arrival and service times and the impact of security incidents on performance was assessed. Typical numerical experiments on the GSPN model were conducted and implemented using the Möbius package, and an ‘optimal’ trade-offs were determined between performance and security, which are crucial in the SLA of the cloud computing services. / Petroleum technology development fund (PTDF) of the government of Nigeria Usmanu Danfodiyo University, Sokoto