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

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No / Security mechanisms, such as encryption and authentication protocols, require extra computing resources and therefore, have an adverse effect upon the performance of robotic mobile wireless ad hoc networks (RANETs). Thus, an optimal performance and security trade-off should be one of the main aspects that should be taken into consideration during the design, development, tuning and upgrading of such networks. In this context, an exposition is initially undertaken on the applicability of Petri nets (PNs) and queueing networks (QNs) in conjunction with their generalisations and hybrid integrations as robust quantitative modelling tools for the performance analysis of discrete flow systems, such as computer systems, communication networks and manufacturing systems. To overcome some of the inherent limitations of these models, a novel hybrid modelling framework is explored for the quantitative evaluation of RANETs, where each robotic node is represented by an abstract open hybrid G-GSPN_QN model with head-of-line priorities, subject to combined performance and security metrics (CPSMs). The proposed model focuses on security processing and state-based control and it is based on an open generalised stochastic PN (GSPN) with a gated multi-class 'On-Off' traffic and mobility model. Moreover, it employs a power consumption model and is linked in tandem with an arbitrary QN consisting of finite capacity channel queues with blocking for 'intra' robot component-to-component communication and 'inter' robot-to-robot transmission. Conclusions and future research directions are included.

Cette thèse est une thèse CIFRE entre le LORIA et la société MEDETIC et porte sur la conception des systèmes de télésurveillance pour le maintien à domicile des personnes âgées.Le système est conçu aux personnes âgées qui veulent passer leur vieillesse dans leur propre maison, à cause de son potentiel pour augmenter l'indépendance et la qualité de la vie. Cela profiterait non seulement aux personnes âgées qui veulent vivre dans leur propre maison, mais aussi le système de santé publique en coupant des prix de façon significative.Mis à part la conception d'une architecture de télésurveillance « Vill’Âge® »basée sur des réseaux de capteurs hétérogènes (Domotique, IEEE802.15.4/Zigbee, Wifi, Bluetooth), la thèse a contribué essentiellement sur la proposition d'un protocole de clustering et de routage dans le réseau de capteurs sans fil avec une approche de la logique floue, et d'un middleware pour la collecte et le traitement des données des capteurs avec la gestion de la qualité de service comme particularité.Une première plateforme de test à été développée à Colmar (MEDETIC) et une seconde, plus complète et fait suite de cette thèse, est en cours de développement au LORIA (http://infositu.loria.fr/).Nous avons participé dans le concours de ministère de l'Enseignement supérieur et de la recherche avec un projet intitulé MPIGate: « Multi Protocol Interface and Gateway for telecare, environment Monitoring and Control » et nous avons gagné le prix de ce concours au niveau d’émergence. / This thesis is a thesis CIFRE between LORIA and the MEDETIC Company and focuses on the design of telehomecare system for the elderly.In addition to the design of a remote surveillance architecture “Vill’Âge ®” based on networks of heterogeneous sensor (home automation, IEEE802.15.4/Zigbee, Wifi, Bluetooth), thesis has contributed essentially on the proposal of a clustering and routing protocol in the network of wireless sensors with an approach to fuzzy logic, and of a middleware for the collection and processing of data from sensors with the management of the quality of service as a special feature.A first platform was developed at Colmar (MEDETIC) and a second who is more complete is under development at LORIA (http://infositu.loria.fr/).By using this system, MEDeTIC, offers a new concept of smart homes for the senior citizens, named in French “Maisons Vill’Âge”. The first housing schemes are being built in 2 departments of France. A flat is entirely equipped to act as a demonstrator and as laboratory of research and development.The system is designed for the elderly who wish to spend their old age in their own home, because of its potential to increase independence and quality of life. This would not only benefit the elderly who want to live in their own home, but also the national health care system by cutting costs significantly. Based on this PhD thesis, MPIGate, a “Multiprotocol Interface and Gateway for for telecare, environment”, has been developed. MPIGate was awarded in the competition of the Ministry of Higher Education and Research and OSEO 2010

Dans le domaine des réseaux de capteurs sans-fil (dits « WSN »), les piles réseau spécialisées constituent un domaine de recherche très actif depuis maintenant de nombreuses années. Toutefois, beaucoup de ces études, notamment concernant les couches basses de ces piles réseau, n’ont pas dépassé le stade de la théorie. Leurs implantations n’ont sauf exception pas fait l’objet d’efforts poussés ou systématiques, surtout dans le cadre des systèmes d’exploitation spécialisés. Nous nous proposons donc, dans cette thèse, de nous focaliser sur l’analyse des interactions entre les protocoles des couches basses et les plates-formes logicielles dédiées, et de les optimiser, notamment au niveau de l’implantation. Nous passons d’abord en revue et évaluons les différents systèmes d’exploitation spécialisés, et choisissons celui offrant les fonctionnalités, notamment temps-réel, que nous estimons nécessaires pour implanter des protocoles MAC / RDC novateurs et performants. Nous entreprenons ensuite un effort d’étude, d’amélioration et d’optimisation de ces couches basses des piles spécialisées, et montrons, avec une implantation concrète d’un de nos protocoles MAC / RDC avancés, que nous pouvons amener des progrès notables dans la qualité de service (QdS) des WSN, notamment avec un trafic réseau intense. Nous examinons en outre des inexactitudes inattendues dans les simulations / émulations effectuées par Cooja / MSPSim, et analysons les problèmes de fiabilité posés par l’utilisation de cet outil pour effectuer des évaluations de performances, notamment temporelles, de WSN. Nous proposons enfin de nouvelles pistes pour de futures améliorations et optimisations de ces couches basses des piles réseau spécialisées, afin d’améliorer encore la fiabilité, les performances et la consommation énergétique des WSN. / In the field of wireless sensors networks (WSN), specialized network stacks have been a very active research field for many years. However, most of this research, especially on lower layers of the network stacks, did not go beyond theory. Their implementations have generally not been the subject of deep or systematic effort, especially within the framework of dedicated operating systems. We thus propose, in this thesis, to focus on interaction analysis between lower layers’ protocols and dedicated software platforms, and to optimize them, especially at the implementation level. We first review and evaluate the various dedicated operating systems, and choose the one offering the necessary features to implement efficient and innovative MAC/RDC protocols. We then study, improve and optimize these lower layers of specialized stacks, and show, with an actual implementation of one of our advanced MAC/RDC protocols, that we can bring significant improvements in the quality of service (QoS) of WSNs, especially under heavy network traffic. We also report inaccuracies in Cooja/MSPSim simulations/emulations, and analyze the reliability issues caused by the use of this tool for performing evaluations (especially time-related) of WSNs. We finally propose some new leads for future enhancements and optimizations of the lower layers of these specialized network stacks, in order to further improve the liability, performances and energy consumption of WSNs.

Made available in DSpace on 2016-04-04T18:31:36Z (GMT). No. of bitstreams: 1 Vitor Chaves de Oliveira.pdf: 1928054 bytes, checksum: 49bf6198a68438069d6ef8b9a2ec77e9 (MD5) Previous issue date: 2012-12-10 / In recent years, virtualization computing has become a worldwide reality present in datacenters servers of most organizations. The motivations for the use of this solution are focused primarily on cost reduction and increases in availability, integrity and security of data. Based on these benefits, recently it was started the use of this technology for personal computers as well. That is, for desktops, giving birth to the so-called desktop virtualization. Given the technical advantages of the approach, its growth has been so significant that, before 2014, it is expected to be present in over 90% of organizations. However, this new method is completely based on a physical client-server architecture, which increases the importance of the communication network that makes this technique possible. Therefore, analyzing the network in order to investigate the effects according to the environment implemented, becomes crucial. In this work it s varied the local s client hardware and the application, i.e. the service used. The purpose was to detail their effects on computer networks in a Quality of Service (QoS) parameter, throughput. Secondarily are outlined perceptions regarding the Quality of Experience (QoE). / Nos ?ltimos anos, a virtualiza??o computacional se tornou uma realidade nos servidores presentes nos data-centers da maioria das organiza??es no mundo. As motiva??es para o emprego desta solu??o est?o centradas, primordialmente, na redu??o de custos e em aumentos na disponibilidade, na integridade e na seguran?a dos dados. Com base nestes benef?cios, recentemente, se come?ou a aproveitar esta tecnologia tamb?m para os computadores pessoais. Isto ?, para os desktops, dando origem a chamada virtualiza??o de desktop. Dadas as vantagen t?cnicas da abordagem, seu crescimento tem sido t?o expressivo que, antes de 2014, se espera que ela esteja presente em mais de 90% das organiza??es. Todavia, este m?todo ? totalmente baseado em uma arquitetura cliente-servidor f?sica, o que aumenta a import?ncia da rede de comunica??o que torna a t?cnica poss?vel. Logo, analisar a rede, a fim de investigar os impactos de acordo com o ambiente implementado, se torna fundamental. Neste trabalho variamos o hardware local do cliente e a aplica??o, isto ?, o servi?o utilizado. A finalidade foi a de detalhar seus efeitos, em redes de computadores, em um par?metro de Qualidade de Servi?o (QoS), a vaz?o. Secundariamente s?o esbo?adas percep??es de Qualidade da Experi?ncia (QoE).

This research study focuses on the application models of Data Mining and Machine Learning covering cellular network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms have been applied on real cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: RStudio for Machine Learning and process visualization, Apache Spark, SparkSQL for data and big data processing and clicData for service Visualization. Two use cases have been studied during this research. In the first study, the process of Data and predictive Analytics are fully applied in the field of Telecommunications to efficiently address users’ experience, in the goal of increasing customer loyalty and decreasing churn or customer attrition. Using real cellular network transactions, prediction analytics are used to predict customers who are likely to churn, which can result in revenue loss. Prediction algorithms and models including Classification Tree, Random Forest, Neural Networks and Gradient boosting have been used with an exploratory Data Analysis, determining relationship between predicting variables. The data is segmented in to two, a training set to train the model and a testing set to test the model. The evaluation of the best performing model is based on the prediction accuracy, sensitivity, specificity and the Confusion Matrix on the test set. The second use case analyses Service Quality Management using modern data mining techniques and the advantages of in-memory big data processing with Apache Spark and SparkSQL to save cost on tool investment; thus, a low-cost Service Quality Management model is proposed and analyzed. With increase in Smart phone adoption, access to mobile internet services, applications such as streaming, interactive chats require a certain service level to ensure customer satisfaction. As a result, an SQM framework is developed with Service Quality Index (SQI) and Key Performance Index (KPI). The research concludes with recommendations and future studies around modern technology applications in Telecommunications including Internet of Things (IoT), Cloud and recommender systems. / Cellular networks have evolved and are still evolving, from traditional GSM (Global System for Mobile Communication) Circuit switched which only supported voice services and extremely low data rate, to LTE all Packet networks accommodating high speed data used for various service applications such as video streaming, video conferencing, heavy torrent download; and for say in a near future the roll-out of the Fifth generation (5G) cellular networks, intended to support complex technologies such as IoT (Internet of Things), High Definition video streaming and projected to cater massive amount of data. With high demand on network services and easy access to mobile phones, billions of transactions are performed by subscribers. The transactions appear in the form of SMSs, Handovers, voice calls, web browsing activities, video and audio streaming, heavy downloads and uploads. Nevertheless, the stormy growth in data traffic and the high requirements of new services introduce bigger challenges to Mobile Network Operators (NMOs) in analysing the big data traffic flowing in the network. Therefore, Quality of Service (QoS) and Quality of Experience (QoE) turn in to a challenge. Inefficiency in mining, analysing data and applying predictive intelligence on network traffic can produce high rate of unhappy customers or subscribers, loss on revenue and negative services’ perspective. Researchers and Service Providers are investing in Data mining, Machine Learning and AI (Artificial Intelligence) methods to manage services and experience. This research study focuses on the application models of Data Mining and Machine Learning covering network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms will be applied on cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: R-Studio for Machine Learning, Apache Spark, SparkSQL for data processing and clicData for Visualization. / Electrical and Mining Engineering / M. Tech (Electrical Engineering)

Multiple-input, multiple-output (MIMO) techniques have been proposed to meet the needs for higher data rates and lower delays in future wireless communication systems. The downlink capacity of multiuser MIMO systems is achieved when the system transmits to several users simultaneously. Frequently, many more users request service than the transmitter can simultaneously support. Thus, the transmitter requires a scheduling algorithm for the users, which must balance the goals of increasing throughput, reducing multiuser interference, lowering delays, ensuring fairness and quality of service (QoS), etc. In this thesis, we investigate the application of genetic algorithms (GAs) to perform scheduling in multiuser MIMO systems. GAs are a fast, suboptimal, low-complexity method of solving optimization problems, such as the maximization of a scheduling metric, and can handle arbitrary functions and QoS constraints. We first examine a system that transmits using capacity-achieving dirty paper coding (DPC). Our proposed GA structure both selects users and determines their encoding order for DPC, which affects the rates they receive. Our GA can also schedule users independently on different carriers of a multi-carrier system. We demonstrate that the GA performance is close to that of an optimal exhaustive search, but at a greatly reduced complexity. We further show that the GA convergence time can be significantly reduced by tuning the values of its parameters. While DPC is capacity-achieving, it is also very complex. Thus, we also investigate GA scheduling with two linear precoding schemes, block diagonalization and successive zero-forcing. We compare the complexity and performance of the GA with "greedy" scheduling algorithms, and find the GA is more complex, but performs better at higher signal-to-noise ratios (SNRs) and smaller user pool sizes. Both algorithms are near-optimal, yet much less complex than an exhaustive search. We also propose hybrid greedy-genetic algorithms to gain benefits from both types of algorithms. Lastly, we propose an improved method of optimizing the transmit covariance matrices for successive zero-forcing. Our algorithm significantly improves upon the performance of the existing method at medium to high SNRs, and, unlike the existing method, can maximize a weighted sum rate, which is important for fairness and QoS considerations. / Communications

Due to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques — effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments.

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