In this thesis, we present two fairly general classes of so called overflow queueing networks. These networks consist of two queues, where the capacity of the first queue is always finite. Customers arriving at the first queue have an overflow capability from the first to the second queue if the first queue operates at a certain fixed capacity, i.e., under certain conditions, demands arriving at the first queue are allowed to join the second queue. The overflow stream will additionally be weighted with a parameter p. This parameter can be used as a control parameter or to model the customers´ impatience. We reduce the number of unknown steady-state probabilities of these system in a considerable amount by a generating functions approach and a separation technique.

La demande des systèmes de communication sans fil pour des débits élevés continue d'augmenter, et il n'y a pas de signes que cette tendance va se ralentir. Trois des techniques les plus importantes qui ont émergé pour répondre à de telles demandes sont l'OFDMA, le relais coopératif et le MIMO. Afin d'utiliser pleinement les capacités des systèmes appliquant de telles techniques, il est essentiel de développer des algorithmes efficaces d'ordonnancement et, plus généralement, des algorithmes efficaces d'allocation de ressources. Les études classiques sur ce sujet examinent des systèmes où les demandes de données des utilisateurs ne sont pas prises en considération et/ou un CSI parfait et complet est supposée être disponible pour le mécanisme d'ordonnancement. Cependant, dans la pratique, différentes limitations peuvent entraîner l'absence d'une connaissance parfaite et/ou complète du CSI, telles que les ressources limitées pour le feedback, le co^ut de sondage et le retard dans le processus de feedback.Par conséquent, dans cette thèse nous examinons les problèmes d'ordonnancement et de feedback sous des considérations réalistes concernant la connaissance du CSI. L'analyse est effectuée au niveau des paquets et considère la dynamique des files d'attente avec des processus d'arrivée arbitraires, et où la mesure de performance principale que nous adoptons est la stabilité des files d'attente. La première partie de la thèse considère un système MIMO multipoint à multipoint utilisant le mode TDD, tout en supposant un backhaul à capacité limitée et en tenant compte du coût du feedback. En ce qui concerne la technique de gestion de l'interférence, nous appliquons l'alignement d'interférence (IA) si plus d'une paire sont actives et SVD si une seule paire est active. La deuxième partie de la thèse considère un système OFDMA avec plusieurs utilisateurs et canaux, où un feedback retardé et limité est pris en compte. Deux scénarios sont étudiés, à savoir le système sans relais et le système avec relais. Pour ce dernier, nous considérons une imperfection supplémentaire supposant que les utilisateurs ont une connaissance incomplète des coefficients du fading entre la station de base et le relais. / Demand of wireless communication systems for high throughputs continues to increase, and there are no signs this trend is slowing down. Three of the most prominent techniques that have emerged to meet such demands are OFDMA, cooperative relaying and MIMO. To fully utilize the capabilities of systems applying such techniques, it is essential to develop eficient scheduling algorithms and, more generally, eficient resource allocation algorithms. Classical studies on this subject investigate in much detail settings where the data requests of the users are not taken into consideration or where the perfect and full CSI is assumed to be available for the scheduling mechanism. In practice, however, diferent limitations may result in not having perfect or full CSI knowledge, such as limited feedback resources, probing cost and delay in the feedback process. Accordingly, in this thesis we examine the problems of scheduling and feedback allocations under realistic considerations concerning the CSI knowledge. Analysis is performed at the packet level and considers the queueing dynamics in the systems with arbitrary arrival processes, where the main performance metric we adopt is the stability of the queues. The first part of the thesis considers a multi-point to multi-point MIMO system with TDD mode under limited backhaul capacity and taking into account the feedback probing cost. Regarding the interference management technique, we apply interference alignment (IA) if more than one pair are active and SVD if only one pair is active. The second part of the thesis considers a multiuser multichannel OFDMA-like system where delayed and limited feedback is accounted for. Two scenarios are investigated, namely the system without relaying and the system with relaying. For the latter one, an additional imperfection we account for is that the users have incomplete knowledge of the fading coeficients between the base-station and the relay.

Doctor Educationis / Cybersecurity defense tools, techniques and methodologies are constantly faced with increasing challenges including the evolution of highly intelligent and powerful new generation threats. The main challenges posed by these modern digital multi-vector attacks is their ability to adapt with machine learning. Research shows that many existing defense systems fail to provide adequate protection against these latest threats. Hence, there is an ever-growing need for self-learning technologies that can autonomously adjust according to the behaviour and patterns of the offensive actors and systems. The accuracy and effectiveness of existing methods are dependent on decision making and manual input by human expert. This dependence causes 1) administration overhead, 2) variable and potentially limited accuracy and 3) delayed response time. In this thesis, Autonomous Threat Detection and Response (ATDR) is a proposed general method aimed at contributing toward security related self-protected networks. Through a combination of unsupervised machine learning and Deep learning, ATDR is designed as an intelligent and autonomous decision-making system that uses big data processing requirements and data frame pattern identification layers to learn sequences of patterns and derive real-time data formations. This system enhances threat detection and response capabilities, accuracy and speed. Research provided a solid foundation for the proposed method around the scope of existing methods and the unanimous problem statements and findings by other authors.

We consider a congestion control problem in computer networks. The problem is posed as an optimal control problem and reduced to a problem of finding solutions to delay differential equations. Systems involving time delays in the dynamics are actually very difficult to model and therefore very difficult to solve. We consider three approaches in our congestion control problem: an elastic queue approach leading to an optimal control problem with a state–dependent delay differential equation; three approaches in flow models (also leading to systems containing delay differential equations), precisely the dual control approach, the primal–dual control approach and the control approach based on queueing delay. The elastic queue approach is not explored due to the lack of software good enough to solve optimal control problems involving delay differential equations. In flow models, we consider the standard case, that is where the feedback from sources to links is exact and the network behaves perfectly well (without any unexpected event). We also consider some non–standard cases such as the case where this feedback contains errors (for example overestimation, underestimation or noise), and the case where one link breaks in the network. We numerically solve the delay differential equations obtained and use the results we get to determine all the considered dynamics in the network. This is followed by an analysis of the results. We also explore the stability of some simple cases in the dual control approach, with weaker conditions on some network parameters, and discuss some fairness conditions in some simple cases in all the flow model approaches. Non–standard cases are also solved numerically and the results can be compared with those obtained in the standard case.

The traffic signal affects the life of virtually everyone every day. The effectiveness of signal systems can reduce the incidence of delays, stops, fuel consumption, emission of pollutants, and accidents. The problems related to rapid growth in traffic congestion call for more effective traffic signalization using robust feedback control methodology. Online traffic-responsive signalization is based on real-time traffic conditions and selects cycle, split, phase, and offset for the intersection according to detector data. A robust traffic feedback control begins with assembling traffic demands, traffic facility supply, and feedback control law for the existing traffic operating environment. This information serves the input to the traffic control process which in turn provides an output in terms of the desired performance under varying conditions. Traffic signalization belongs to a class of hybrid systems since the differential equations model the continuous behavior of the traffic flow dynamics and finite-state machines model the discrete state changes of the controller. A complicating aspect, due to the state-space constraint that queue lengths are necessarily nonnegative, is that the continuous-time system dynamics is actually the projection of a smooth system of ordinary differential equations. This also leads to discontinuities in the boundary dynamics of a sort common in queueing problems. The project is concerned with the design of a feedback controller to minimize accumulated queue lengths in the presence of unknown inflow disturbances at an isolated intersection and a traffic network with some signalized intersections. A dynamical system has finite L₂-gain if it is dissipative in some sense. Therefore, the H<SUB>infinity</SUB>-control problem turns to designing a controller such that the resulting closed loop system is dissipative, and correspondingly there exists a storage function. The major contributions of this thesis include 1) to propose state space models for both isolated multi-phase intersections and a class of queueing networks; 2) to formulate H<SUB>infinity</SUB> problems for the control systems with persistent disturbances; 3) to present the projection dynamics aspects of the problem to account for the constraints on the state variables; 4) formally to study this problem as a hybrid system; 5) to derive traffic-actuated feedback control laws for the multi-phase intersections. Though we have mathematically presented a robust feedback solution for the traffic signalization, there still remains some distance before the physical implementation. A robust adaptive control is an interesting research area for the future traffic signalization. / Ph. D.

No / An investigation is carried out on the nature of QoS measures for queues with correlated traffic in both discrete and continuous time domains. The study focuses on the single server GI(G)/M-[x]/1/N and GI(G)/Geo([x])/1/N queues with finite capacity, N, a general batch renewal arrival process (BRAP), GI(G) and either batch Poisson, M-[x] or batch geometric, Geo([x]) service times with general batch sizes, X. Closed form expressions for QoS measures, such as queue length and waiting time distributions and blocking probabilities are stochastically derived and showed to be, essentially, time domain invariant. Moreover, the sGGeo(sGGo)/Geo/l/N queue with a shifted generalised geometric (sGGeo) distribution is employed to assess the adverse impact of varying degrees of traffic correlations upon basic QoS measures and consequently, illustrative numerical results are presented. Finally, the global balance queue length distribution of the M-Geo/M-Geo/1/N queue is devised and reinterpreted in terms of information theoretic principle of entropy maximisation. (C) 2014 Elsevier Inc. All rights reserved.

Modelling is an important technique in the comprehension and management of complex systems. Queueing network models capture most relevant information from computer system and network behaviour. The construction and resolution of these models is constrained by many factors. Approximations contain detail lost for exact solution and/or provide results at lower cost than simulation. Information at the resource and interactive command level is gathered with monitors under ULTRIX'. Validation studies indicate central processor service times are highly variable on the system. More pessimistic predictions assuming this variability are in part verified by observation. The utility of the Generalised Exponential (GE) as a distribution parameterised by mean and variance is explored. Small networks of GE service centres can be solved exactly using methods proposed for Generalised Stochastic Petri Nets. For two centre. systems of GE type a new technique simplifying the balance equations is developed. A very efficient "building bglloocbka"l. is presented for exactly solving two centre systems with service or transfer blocking, Bernoulli feedback and load dependent rate, multiple GE servers. In the tandem finite buffer algorithm the building block illustrates problems encountered modelling high variability in blocking networks. ': . _. A parametric validation study is made of approximations for single class closed networks of First-Come-First-Served (FCFS) centres with general service times. The multiserver extension using the building block is validated. Finally the Maximum Entropy approximation is extended to FCFS centres with multiple chains and implemented with computationally efficient convolution.

Traditionally the Internet is used for the following applications: FTP, e-mail and Web traffic. However in the recent years the Internet is increasingly supporting emerging applications such as IP telephony, video conferencing and online games. These new applications have different requirements in terms of throughput and delay than traditional applications. For example, interactive multimedia applications, unlike traditional applications, have more strict delay constraints and less strict loss constraints. Unfortunately, the current Internet offers only a best-effort service to all applications without any consideration to the applications specific requirements. In this thesis three existing Active Queue Management (AQM) mechanisms are modified by incorporating into these a control function to condition routers for better Quality of Service (QoS). Specifically, delay is considered as the key QoS metric as it is the most important metric for real-time multimedia applications. The first modified mechanism is Drop Tail (DT), which is a simple mechanism in comparison with most AQM schemes. A dynamic threshold has been added to DT in order to maintain packet queueing delay at a specified value. The modified mechanism is referred to as Adaptive Drop Tail (ADT). The second mechanism considered is Early Random Drop (ERD) and, iii in a similar way to ADT, a dynamic threshold has been used to keep the delay at a required value, the main difference being that packets are now dropped probabilistically before the queue reaches full capacity. This mechanism is referred to as Adaptive Early Random Drop (AERD). The final mechanism considered is motivated by the well known Random Early Detection AQM mechanism and is effectively a multi-threshold version of AERD in which packets are dropped with a linear function between the two thresholds and the second threshold is moveable in order to change the slope of the dropping function. This mechanism is called Multi Threshold Adaptive Early Random Drop (MTAERD) and is used in a similar way to the other mechanisms to maintain delay around a specified level. The main focus with all the mechanisms is on queueing delay, which is a significant component of end-to-end delay, and also on reducing the jitter (delay variation) A control algorithm is developed using an analytical model that specifies the delay as a function of the queue threshold position and this function has been used in a simulation to adjust the threshold to an effective value to maintain the delay around a specified value as the packet arrival rate changes over time. iv A two state Markov Modulated Poisson Process is used as the arrival process to each of the three systems to introduce burstiness and correlation of the packet inter-arrival times and to present sudden changes in the arrival process as might be encountered when TCP is used as the transport protocol and step changes the size of its congestion window. In the investigations it is assumed the traffic source is a mixture of TCP and UDP traffic and that the mechanisms conserved apply to the TCP based data. It is also assumed that this consists of the majority proportion of the total traffic so that the control mechanisms have a significant effect on controlling the overall delay. The three mechanisms are evaluated using a Java framework and results are presented showing the amount of improvement in QoS that can be achieved by the mechanisms over their non-adaptive counterparts. The mechanisms are also compared with each other and conclusions drawn.

No description available.

<p>This thesis details the development of a kinetic model of translation which takes into account codon usage. The process of translation involves ribosomes decoding a sequence of codons to produce a protein. Codon usage is important in the kinetics of translation since experiments have shown that codons are processed at different rates. Codons which code for the same amino acid appear with unequal frequencies and certain synonymous codons are preferred by high expression genes. The relationship between translational efficiency and codon adaptation is explored in this thesis.</p> <p>We use a simple physics model called the totally asymmetric exclusion process (TASEP) to emulate the action of ribosomes, and the decoding of mRNA in protein elongation. The simple model is parameterized by an initiation rate that determines how quickly new ribosomes are introduced onto the lattice, and the rate of motion for ribosomes associated with a site on the lattice (codon message). Based on bioinformatics studies, we assign codon speeds so that codons preferred by high expression genes are translated more quickly.</p> <p>The model captures important aspects of translation like ribosome collision and codons of different speeds, and simulating it allows us to see details in dynamics which are inaccessible to experiments. TASEP has non-trivial behaviour when codon rates, and the rate of ribosome binding is varied. Slow codons can cause ribosomes to pause and may lead to a queue. We approximated real genes with its average rate, and with its slowest codons to test the salient features of how codons are used on mRNAs. We found that codon selection is important in determining when queues occur, and the ribosome density on genes. The model also shows that highly expressed genes queue later than low expression genes. The simple model gives us general insights into the translational selection of codons, and the important kinetic parameters.</p> / Master of Science (MSc)