Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.

Lors d'une communication dans un réseau, les nœuds intermédiaires se contentent en général de retransmettre les paquets de données qu'ils reçoivent. Grâce au codage de réseau (NC), ces nœuds intermédiaires peuvent envoyer des combinaisons linéaires des paquets qu'ils ont reçus. Ceci permet une meilleure exploitation de la capacité du réseau et une plus grande robustesse à l'égard de pertes.Cette thèse s'intéresse à une implantation du NC en lien avec TCP (TCP-NC). Grâce à la redondance introduite par le NC, une partie des pertes liées à des liens sans fils peut être compensée. Elle propose en particulier un mécanisme d'adaptation de la redondance introduite par le codage de réseau. Une première partie de cette thèse est consacrée à l'analyse de la dynamique de TCP-NC avec Random Early Detection (RED) comme mécanisme de gestion des files d'attente en utilisant les outils d'optimisation convexe et issus de l’automatique. Nous caractérisons l'équilibre du réseau et les propriétés de stabilité de TCP-Reno en présence de NC. Dans une seconde partie, cette thèse propose un algorithme d'adaptation de la redondance introduite par NC. Dans TCP-NC avec redondance adaptative (TCP-NCAR), cet ajustement se fait grâce à un schéma de différenciation des pertes, qui estime la répartition des pertes entre erreurs de transmission dues aux liens sans fils et pertes liées à la congestion. Les propriétés d'équilibre et de stabilité de TCP-NCAR/RED sont caractérisées. Les résultats théoriques et de simulation montrent que TCP-NCAR adopte une redondance proche de l'optimum quand les taux de perte de paquets sur les liens sans fils sont petits. En outre, le modèle linéarisé autour de l'équilibre montre que TCP-NCAR augmente la taille de la région de stabilité de TCP-Reno. / Communication networks today share the same fundamental principle of operation: information is delivered to their destination by nodes intermediate in a store-and-forward manner.Network coding (NC) is a technique that allows intermediate nodes to send out packets that are linear combinations of previously received information. The main benefits of NC are the potential throughput improvements and a high degree of robustness, which is translated into loss resilience. These benefits have motivated deployment efforts for practical applications of NC, e.g., incorporating NC into congestion control schemes such as TCP-Reno to get a TCP-NC congestion protocol. In TCP-NC, TCP-Reno throughput is improved by sending a fixed amount of redundant packets, which mask part of the losses due, e.g., to channel transmission errors. In this thesis, we first analyze the dynamics of TCP-NC with random early detection (RED) as active queue management (AQM) using tools from convex optimization and feedback control. We study the network equilibrium point and the stability properties of TCP-Reno when NC is incorporated into the TCP/IP protocol stack. The existence and uniqueness of an equilibrium point is proved, and characterized in terms of average throughput, loss rate, and queue length. Our study also shows that TCP-NC/RED becomes unstable when delay or link capacities increases, but also, when the amount of redundant packets added by NC increases. Using a continuous-time model and neglecting feedback delays, we prove that TCP-NC is globally stable. We provide a sufficient condition for local stability when feedback delays are present. The fairness of TCP-NC with respect to TCP-Reno-like protocols is also studied. Second, we propose an algorithm to dynamically adjust the amount of redundant linear combinations of packets transmitted by NC. In TCP-NC with adaptive redundancy (TCP-NCAR), the redundancy is adjusted using a loss differentiation scheme, which estimates the amount of losses due to channel transmission errors and due to congestion. Simulation results show that TCP-NCAR outperforms TCP-NC in terms of throughput. Finally, we analyze the equilibrium and stability properties of TCP-NCAR/RED. The existence and uniqueness of an equilibrium point is characterized experimentally. The TCP-NCAR/RED dynamics are modeled using a continuous-time model. Theoretical and simulation results show that TCP-NCAR tracks the optimal value for the redundancy for small values of the packet loss rate. Moreover, simulations of the linearized model around equilibrium show that TCP-NCAR increases the size of the TCP-Reno stability region. We show that this is due to the compensator effect of the redundancy adaptation dynamics to TCP-Reno. These characteristics of TCP-NCAR allow the congestion window adaptation mechanism of TCP-Reno to react in a smooth way to channel losses, avoiding some unnecessary rate reductions, and increasing the local stability of TCP-Reno.

Cette thèse se focalise sur le développement des algorithmes d’ordonnancement sous contrainte (m, k)-firm, ainsi que leurs applications pour la gestion de la qualité de service (QdS) dans les réseaux et systèmes temps réel distribués. L’objectif recherché est la garantie déterministe de la QdS tout en maintenant un fort taux d’utilisation des ressources. Les contributions sont (1) l’établissement d’une condition suffisante d’ordonnançabilité d'un ensemble de tâches sous l’algorithme « distance based priority »; (2) la définition de R-(m, k)-firm, un nouveau modèle qui relâche la contrainte (m, k)-firm et qui permet de modéliser de façon plus juste des exigences du temps réel souple; (3) le développement d’un algorithme efficace de dimensionnement de ressources sous contrainte (m, k)-firm relâchée; (4) la proposition de « Double Leaks Bucket » pour la gestion active de files d'attente permettant de maintenir une QdS en cas de surcharge des réseaux / This work focuses on the scheduling algorithms under (m,k)-firm constraint, as well as the applications for QoS (quality of service) management in the networks and distributed real-time system. The research aim is to achieve the deterministic guarantee of QoS with high resource utilization. The contributions in this thesis include (1) proposing a sufficient condition for determining the schedulability of a real-time task set under Distance Base Priority scheduling algorithm; (2) defining a novel real-time constraint which relaxes the (m,k)-firm constraint and provides a more suitable modelling of soft real-time; (3) developing an effective resource provisioning algorithm under this relaxed (m,k)-firm constraint; (4) proposing an active queue management mechanism, called Double Leaks Bucket, which can guarantee the QoS with dynamic dropping of the packets during the networks overload period

"The Internet has assumed the role of the underlying communication network for applications such as file transfer, electronic mail, Web browsing and multimedia streaming. Multimedia streaming, in particular, is growing with the growth in power and connectivity of today's computers. These Internet applications have a variety of network service requirements and traffic characteristics, which presents new challenges to the single best-effort service of today's Internet. TCP, the de facto Internet transport protocol, has been successful in satisfying the needs of traditional Internet applications, but fails to satisfy the increasingly popular delay sensitive multimedia applications. Streaming applications often use UDP without a proper congestion avoidance mechanisms, threatening the well-being of the Internet. This dissertation presents an IP router traffic management mechanism, referred to as Crimson, that can be seamlessly deployed in the current Internet to protect well-behaving traffic from misbehaving traffic and support Quality of Service (QoS) requirements of delay sensitive multimedia applications as well as traditional Internet applications. In addition, as a means to enhance Internet support for multimedia streaming, this dissertation report presents design and evaluation of a TCP-Friendly and streaming-friendly transport protocol called the Multimedia Transport Protocol (MTP). Through a simulation study this report shows the Crimson network efficiently handles network congestion and minimizes queuing delay while providing affordable fairness protection from misbehaving flows over a wide range of traffic conditions. In addition, our results show that MTP offers streaming performance comparable to that provided by UDP, while doing so under a TCP-Friendly rate."

Active queue management (AQM) techniques for congestion control in Internet Protocol (IP) networks have been designed using both heuristic and analytical methods. But so far, there has been found no AQM scheme designed in the realm of stochastic optimization. Of the many options available in this arena, the gradient-based stochastic approximation method using Infintesimal Perturbation Analysis (IPA) gradient estimators within the Stochastic Fluid Model (SFM) framework is very promising. The research outlined in this thesis provides the theoretical basis and foundational layer for the development of IPA-based AQM schemes. Algorithms for computing the IPA gradient estimators for loss volume and queue workload were derived for the following cases: a single-stage queue with instantaneous, additive loss-feedback, a single-stage queue with instantaneous, additive loss-feedback and an unresponsive competing flow, a single-stage queue with delayed, additive loss-feedback, and a multi-stage tandem network of $m$ queues with instantaneous, additive loss-feedback. For all cases, the IPA gradient estimators were derived with the control parameter, $ heta$, being the buffer-limits of the queue(s). For the single-stage case and the multi-stage case with instantaneous, additive loss-feedback, the IPA gradient estimators for when the control parameter, $ heta$, is the loss-feedback constant, were also derived. Sensitivity analyses and optimizations were performed with control parameter, $ heta$, being the buffer-limits of the queue(s), as well as the loss-feedback constant.

Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.

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

As the electricity demand increases dramatically in Sweden, the need of using the existing electricity grid as efficiently as possible gains more importance. Simultaneously as needs expand, so does production in the form of wind parks and solar parks. This has led to an increase in connection requests at Svenska Kraftnät, the Swedish transmission system operator. The current process for accepting or rejecting these requests is based on the first-come-first-serve principle, where each request is investigated separately. This thesis investigates an alternative way of processing the requests in clusters and optimizing which combination is the best to accept from a technical point of view. To handle this multiobjective combinatorial optimization problem, a multiobjective Genetic algorithm with a Pareto filter is developed. The Genetic Algorithm finds a refined Pareto front containing optimal solutions that are plotted with objective function values. The user can then easily analyze the optimal solutions and decide upon which the final optimal request combination is. The developed Genetic Algorithm reaches a close-optimal Pareto front estimation after exploring between 15-40% of the solution space.

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Along with playing an ever-increasing role in the integration of other communication networks and expanding in application diversities, the current Internet suffers from serious overuse and congestion bottlenecks. Efficient congestion control is fundamental to ensure the Internet reliability, satisfy the specified Quality-of-Service (QoS) constraints and achieve desirable performance in response to varying application scenarios. Active Queue Management (AQM) is a promising scheme to support end-to-end Transmission Control Protocol (TCP) congestion control because it enables the sender to react appropriately to the real network situation. Analytical performance models are powerful tools which can be adopted to investigate optimal setting of AQM parameters. Among the existing research efforts in this field, however, there is a current lack of analytical models that can be viewed as a cost-effective performance evaluation tool for AQM in the presence of heterogeneous traffic, generated by various network applications. This thesis aims to provide a generic and extensible analytical framework for analyzing AQM congestion control for various traffic types, such as non-bursty Poisson and bursty Markov-Modulated Poisson Process (MMPP) traffic. Specifically, the Markov analytical models are developed for AQM congestion control scheme coupled with queue thresholds and then are adopted to derive expressions for important QoS metrics. The main contributions of this thesis are listed as follows: • Study the queueing systems for modeling AQM scheme subject to single-class and multiple-classes Poisson traffic, respectively. Analyze the effects of the varying threshold, mean traffic arrival rate, service rate and buffer capacity on the key performance metrics. • Propose an analytical model for AQM scheme with single class bursty traffic and investigate how burstiness and correlations affect the performance metrics. The analytical results reveal that high burstiness and correlation can result in significant degradation of AQM performance, such as increased queueing delay and packet loss probability, and reduced throughput and utlization. • Develop an analytical model for a single server queueing system with AQM in the presence of heterogeneous traffic and evaluate the aggregate and marginal performance subject to different threshold values, burstiness degree and correlation. • Conduct stochastic analysis of a single-server system with single-queue and multiple-queues, respectively, for AQM scheme in the presence of multiple priority traffic classes scheduled by the Priority Resume (PR) policy. • Carry out the performance comparison of AQM with PR and First-In First-Out (FIFO) scheme and compare the performance of AQM with single PR priority queue and multiple priority queues, respectively.