The Transmission Control Protocol (TCP) is the dominant transport protocol in today?s Internet. The original design of TCP left congestion control open to future designers. Short of implementing changes to the TCP stack on the end-nodes themselves, Internet Service Providers have employed several techniques to be able to operate their network equipment efficiently. These techniques amount to shaping traffic to reduce cost and improve overall customer satisfaction. <br /><br /> The method that gives maximum control when performing traffic shaping is using an inline traffic shaper. An inline traffic shaper sits in the middle of any flow, allowing packets to pass through it and, with policy-limited freedom, inspects and modifies all packets as it pleases. However, a number of practical issues such as hardware reliability or ISP policy, may prevent such a solution from being employed. For example, an ISP that does not fully trust the quality of the traffic shaper would not want such a product to be placed in-line with its equipment, as it places a significant threat to its business. What is required in such cases is third-party rate control. <br /><br /> Formally defined, a third-party rate controller is one that can see all traffic and inject new traffic into the network, but cannot remove or modify existing network packets. Given these restrictions, we present and study a technique to control TCP flows, namely triple-ACK duplication. The triple-ACK algorithm allows significant capabilities to a third-party traffic shaper. We provide an analytical justification for why this technique works under ideal conditions and demonstrate via simulation the bandwidth reduction achieved. When judiciously applied, the triple-ACK duplication technique produces minimal badput, while producing significant reductions in bandwidth consumption under ideal conditions. Based on a brief study, we show that our algorithm is able to selectively throttle one flow while allowing another to gain in bandwidth.

The Transmission Control Protocol (TCP) is the dominant transport protocol in today?s Internet. The original design of TCP left congestion control open to future designers. Short of implementing changes to the TCP stack on the end-nodes themselves, Internet Service Providers have employed several techniques to be able to operate their network equipment efficiently. These techniques amount to shaping traffic to reduce cost and improve overall customer satisfaction. <br /><br /> The method that gives maximum control when performing traffic shaping is using an inline traffic shaper. An inline traffic shaper sits in the middle of any flow, allowing packets to pass through it and, with policy-limited freedom, inspects and modifies all packets as it pleases. However, a number of practical issues such as hardware reliability or ISP policy, may prevent such a solution from being employed. For example, an ISP that does not fully trust the quality of the traffic shaper would not want such a product to be placed in-line with its equipment, as it places a significant threat to its business. What is required in such cases is third-party rate control. <br /><br /> Formally defined, a third-party rate controller is one that can see all traffic and inject new traffic into the network, but cannot remove or modify existing network packets. Given these restrictions, we present and study a technique to control TCP flows, namely triple-ACK duplication. The triple-ACK algorithm allows significant capabilities to a third-party traffic shaper. We provide an analytical justification for why this technique works under ideal conditions and demonstrate via simulation the bandwidth reduction achieved. When judiciously applied, the triple-ACK duplication technique produces minimal badput, while producing significant reductions in bandwidth consumption under ideal conditions. Based on a brief study, we show that our algorithm is able to selectively throttle one flow while allowing another to gain in bandwidth.

Multicast has long been considered an attractive service for the Internet for the provision of multiparty applications. For over a decade now multicast has been a proposed IETF standard. Though there is a strong industry push towards deploying multicast, there has been little multicast deployment by commercial Internet Service Providers (ISPs) and more importantly most end-users still lack multicast capabilities. Depending on the underlying network infrastructure, the ISP has several options of implementing his multicast capabilities. With significantly faster and more sophisticated protocols being designed and prototyped, it is expected that a whole new gamut of applications that are delay sensitive will come into being. However, the incentives to resolve the conflicting interests of the ISPs and the end-users have to be provided for successful implementation of these protocols. Thus we arrive at the following economic questions: What is the strategy that will enable the ISP recover his costs ? How can the end-user be made aware of the cost of his actions ? Naturally, the strategies of the ISP and the end-user depend on each other and form an economic game. The research problems addressed in this thesis are: A pricing model that is independent of the underlying transmission protocols is prefered. We have proposed such a pricing scheme for multicast independent of the underlying protocols, by introducing the concept of pricing points* These pricing points provide a range of prices that the users can expect during a particular time period and tune their usage accordingly. Our pricing scheme makes both the sender and receiver accountable. Our scheme also provides for catering to heterogeneous users and gives incentive for differential pricing. We explore a number of formulations of resource allocation problems arising in communication networks as optimization models. Optimization-based methods were only employed for unicast congestion control. We have extended this method for single rate multicast. We have also devised an optimization-based approach for multicast congestion control that finds an allocation rate to maximize the social welfare. Finally we also show that the session-splitting problem can also be cast as an optimization problem. The commonly used "max-min" fairness criteria suffers from serious limitations like discriminating sessions that traverse large number of links and poor network utilization. We provide an allocation scheme that reduces discrimination towards multicast sessions that traverse many links and also improves network utilization.

We study the problem of joint congestion control, routing and MAC layer scheduling in multi-hop wireless mesh networks, where the nodes in the network are subjected to energy expenditure rate constraints. As wireless scenario does not allow all the links to be active all the time, only a subset of given links can be active simultaneously. We model the inter-link interference using the link contention graph. All the nodes in the network are power-constrained and we model this constraint using energy expenditure rate matrix. Then we formulate the problem as a network utility maximization (NUM) problem. We notice that this is a convex optimization problem with affine constraints. We apply duality theory and decompose the problem into two sub-problems namely, network layer congestion control and routing problem, and MAC layer scheduling problem. The source adjusts its rate based on the cost of the least cost path to the destination where the cost of the path includes not only the prices of the links in it but also the prices associated with the nodes on the path. The MAC layer scheduling of the links is carried out based on the prices of the links. The optimal scheduler selects that set of non-interfering links, for which the sum of link prices is maximum. We study the effects of energy expenditure rate constraints of the nodes on the maximum possible network utility. It turns out that the dominant of the two constraints namely, the link capacity constraint and the node energy expenditure rate constraint affects the network utility most. Also we notice the fact that the energy expenditure rate constraints do not affect the nature of optimal link scheduling problem. Following this fact, we study the problem of distributed link scheduling. Optimal scheduling requires selecting independent set of maximum aggregate price, but this problem is known to be NP-hard. We first show that as long as scheduling policy selects the set of non-interfering links, it can not go unboundedly away from the optimal solution of network utility maximization problem. Then we proceed and evaluate a simple greedy scheduling algorithm. Analytical bounds on performance are provided and simulations indicate that the greedy heuristic performs well in practice.

Each day, Humanity loses thousands of persons on roads when they were traveling to work, to study or even to distract. The financial cost of these injuries is also terrifying: Some statistics evaluate the financial cost of vehicle accidents at 160 billion Euro in Europe each year. These alarming figures have driven researchers, automotive companies and public governments to improve the safety of our transportation systems and communication technologies aiming at offering safer roads and smooth driving to human beings. In this context, Vehicular Adhoc Networks, where vehicles are able to communicate with each others and with existent road side units, emerge as a promising wireless technology able to enhance the vision of drivers and offer larger telematic horizon. VANETs promising applications are not only restricted to road safety but span from vehicle trafficoptimization like flow congestion control to commercial applications like file sharing and internet access. Safety applications require that their alert information is propagated to the concerned vehicles (located in the hazardous zone) with little delay and high reliability. For these reasons, this category of applications is considered as delay sensitive and broadcast-oriented nature. While classical blind flooding is rapid, its major drawback is its huge bandwidth utilization. In this thesis, we are interested on enhancing vehicular communications under different scenarios and optimizations: First, We focus on deriving a new solution (EBDR) to disseminate alert messages among moving vehicles while maintaining it efficient and rapid. Our proposal is based on directional antennas to broadcast messages and a route guidance algorithm to choose the best path for the packets. Findings confirmed the efficiency of our approach in terms of probability of success and end-to-end delays. Moreover, in spite of the broadcast nature of the proposed technique, all transmissions stop very soon after the arrival of a packet to its destination representing a strong feature in the conception of EBDR. Second, we propose a novel mathematical framework to evaluate the performance of EBDR analytically. Although most of the proposed techniques present in literature use experimental or simulation tools to defend their performance, we rely here on mathematical models to confirm our achieved results. Our proposed framework allows to derive meaningful performance metrics including the probability of transmission success and the required number of hops to reach thefinal destination. Third, we refine our proposed broadcast-based routing EBDR to provide more efficient broadcasting by adjusting the transmission range of each vehicle based on its distance to the destination and the local node density. This mechanism allows better minimization of interferences and bandwidth's saving. Furthermore, an analytical model is derived to calculate thetransmission area in the case of a simplified node distribution. Finally, we are interested on data collection mechanisms as they make inter-vehicle communications more efficient and reliable and minimize the bandwidth utilization. Our technique uses Q-learning to collect data among moving vehicles in VANETs. The aim behind using the learning technique is to make the collecting operation more reactive to nodes mobility and topology changes. For the simulation part, we compare it to a non-learning version to study the effect of the learning technique. Findings show that our technique far outperforms other propositions and achieves a good trade off between delay and collection ratio. In conclusion, we believe that the different contributions presented in this Thesis will improve the efficiency of inter-vehicle communications in both dissemination and data collection directions. In addition, our mathematical contributions will enrich the literature in terms of constructing suitable models to evaluate broadcasting techniques in urban zones

An ever increasing demand for instant and reliable information on modern communication networks forces codewords to operate in a non-asymptotic regime. To achieve reliability for imperfect channels in this regime, codewords need to be retransmitted from receiver to the transmit buffer, aided by a fast feedback mechanism. Large occupancy of this buffer results in longer communication delays. Therefore, codewords need to be designed carefully to reduce transmit queue-length and thus the delay experienced in this buffer. We first study the consequences of physical layer decisions on the transmit buffer occupancy. We develop an analytical framework to relate physical layer channel to the transmit buffer occupancy. We compute the optimal code-rate for finite-length codewords operating over a correlated channel, under certain communication service guarantees. We show that channel memory has a significant impact on this optimal code-rate. Next, we study the delay in small ad-hoc networks. In particular, we find out what rates can be supported on a small network, when each flow has a certain end-to-end service guarantee. To this end, service guarantee at each intermediate link is characterized. These results are applied to study the potential benefits of setting up a network suitable for network coding in multicast. In particular, we quantify the gains of network coding over classic routing for service provisioned multicast communication over butterfly networks. In the wireless setting, we study the trade-off between communications gains achieved by network coding and the cost to set-up a network enabling network coding. In particular, we show existence of scenarios where one should not attempt to create a network suitable for coding. Insights obtained from these studies are applied to design a distributed rate control algorithm in a large network. This algorithm maximizes sum-utility of all flows, while satisfying per-flow end-to-end service guarantees. We introduce a notion of effective-capacity per communication link that captures the service requirements of flows sharing this link. Each link maintains a price and effective-capacity, and each flow maintains rate and dissatisfaction. Flows and links update their respective variables locally, and we show that their decisions drive the system to an optimal point. We implemented our algorithm on a network simulator and studied its convergence behavior on few networks of practical interest.

Recently, there has been a significant rise in the Hyper-Text Transfer Protocol (HTTP) video streaming usage worldwide. However, the knowledge of performance of HTTP video streaming is still limited, especially in the aspect of factors which affect video quality. The reason is that HTTP video streaming has different characteristics from other video streaming systems. In this thesis, we show how the delivered quality of a Flash video playback is affected by different factors from diverse layers of the video delivery system, including congestion control algorithm, delay variation, playout buffer length, video bitrate and so on. We introduce Quality of Delivery Degradation (QoDD) then we use it to measure how much the Quality of Delivery (QoD) is degraded in terms of QoDD. The study is processed in a dedicated controlled environment, where we could alter the influential factors and then measure what is happening. After that, we use statistic method to analyze the data and find the relationships between influential factors and quality of video delivery which are expressed by mathematic models. The results show that the status and choices of factors have a significant impact on the QoD. By proper control of the factors, the quality of delivery could be improved. The improvements are approximately 24% by TCP memory size, 63% by congestion control algorithm, 30% by delay variation, 97% by delay when considering delay variation, 5% by loss and 92% by video bitrate.

Chaque jour, l'humanité perd des milliers de personnes sur les routes pendant qu'ils se rendaient à travailler, à étudier ou même à se distraire. Ce nombre alarmant s'accumule avec le coût financier terrifiant de ces décès: Certaines statistiques évaluent le coût à 160 milliards d'euros par an en Europe. Dans ce contexte, les réseaux véhiculaires (VANETs) émergent comme une technologie sans fil prometteuse capable d'améliorer la vision des conducteurs et ainsi offrir un horizon télématique plus vaste. Les applications de sécurité routière exigent que le message d'alerte soit propagé de proche en proche par les véhicules jusqu'à arriver à la zone concernée par l'alerte tout en respectant les délais minimaux exigés par ce type d'applications et la grande fiabilité des transmissions. Dans cette thèse, nous nous intéressons à l'amélioration de l'efficacité des communications inter-véhiculaires sous différents scénarios: tout d'abord, nous nous concentrons sur le développement d'une nouvelle solution, appelée EBDR, pour disséminer les informations d'alertes dans un réseau VANET tout en assurant des courts délais de bout en bout et une efficacité pour les transmissions. Notre proposition est basée sur des transmissions dirigées effectuées à l'aide des antennes directionnelles pour la diffusion des messages et un algorithme de guidage d'itinéraire afin de choisir le meilleur chemin pour le paquet. En dépit de son fonctionnement en diffusion, les transmissions de notre technique s'arrêtent très rapidement après l'arrivée du paquet à la destination finale ce qui représente une caractéristique fondamentale dans la conception d’EBDR. Deuxièmement, nous proposons un framework mathématique ayant pour objectif l'évaluation des performances d’EBDR analytiquement. Nos modèles analytiques permettent de dériver des métriques de performances significatives à savoir la probabilité de succès et le nombre de sauts requis pour atteindre la destination finale. En outre, nous proposons une amélioration de notre protocole EBDR dans le but de fournir une diffusion plus efficace. Pour cela, nous nous basons sur l'ajustement de la puissance de transmission de chaque véhicule en fonction de la distance qui le sépare de la destination et la densité locale des nœuds. Ce mécanisme de contrôle de congestion permet de mieux minimiser les interférences et économiser de la bande passante. En plus, un modèle mathématique a été élaboré pour calculer la surface de la zone de transmission dans le cas d'une distribution uniforme des nœuds. Finalement, nous nous sommes intéressés aux mécanismes de collecte de données dans les réseaux véhiculaires. Notre approche est basée sur l'utilisation du principe du Q-learning pour la collecte des données des véhicules en mouvement. L'objectif de l'utilisation de ce mécanisme d'apprentissage est de rendre l'opération de collecte mieux adaptée à la mobilité des nœuds et le changement rapide de la topologie du réseau. Notre technique a été comparée à des méthodes n'utilisant pas du "learning", afin d'étudier l'effet du mécanisme d'apprentissage. Les résultats ont montré que notre approche dépasse largement les autres propositions en terme de performances et réalise un bon compromis entre le taux de collecte et les délais de bout en bout. Pour conclure, nous pensons que nos différentes contributions présentées tout le long de cette thèse permettront d'améliorer l'efficacité des communications sans fil inter-véhiculaires dans les deux directions de recherches ciblées par cette thèse à savoir : la dissémination des messages et la collecte des données. En outre, nos contributions de modélisation mathématique enrichiront la littérature en termes de modèles analytiques capables d'évaluer les techniques de transmission des données dans un réseau véhiculaire / Each day, Humanity loses thousands of persons on roads when they were traveling to work, to study or even to distract. The financial cost of these injuries is also terrifying: Some statistics evaluate the financial cost of vehicle accidents at 160 billion Euro in Europe each year. These alarming figures have driven researchers, automotive companies and public governments to improve the safety of our transportation systems and communication technologies aiming at offering safer roads and smooth driving to human beings. In this context, Vehicular Adhoc Networks, where vehicles are able to communicate with each others and with existent road side units, emerge as a promising wireless technology able to enhance the vision of drivers and offer larger telematic horizon. VANETs promising applications are not only restricted to road safety but span from vehicle trafficoptimization like flow congestion control to commercial applications like file sharing and internet access. Safety applications require that their alert information is propagated to the concerned vehicles (located in the hazardous zone) with little delay and high reliability. For these reasons, this category of applications is considered as delay sensitive and broadcast-oriented nature. While classical blind flooding is rapid, its major drawback is its huge bandwidth utilization. In this thesis, we are interested on enhancing vehicular communications under different scenarios and optimizations: First, We focus on deriving a new solution (EBDR) to disseminate alert messages among moving vehicles while maintaining it efficient and rapid. Our proposal is based on directional antennas to broadcast messages and a route guidance algorithm to choose the best path for the packets. Findings confirmed the efficiency of our approach in terms of probability of success and end-to-end delays. Moreover, in spite of the broadcast nature of the proposed technique, all transmissions stop very soon after the arrival of a packet to its destination representing a strong feature in the conception of EBDR. Second, we propose a novel mathematical framework to evaluate the performance of EBDR analytically. Although most of the proposed techniques present in literature use experimental or simulation tools to defend their performance, we rely here on mathematical models to confirm our achieved results. Our proposed framework allows to derive meaningful performance metrics including the probability of transmission success and the required number of hops to reach thefinal destination. Third, we refine our proposed broadcast-based routing EBDR to provide more efficient broadcasting by adjusting the transmission range of each vehicle based on its distance to the destination and the local node density. This mechanism allows better minimization of interferences and bandwidth's saving. Furthermore, an analytical model is derived to calculate thetransmission area in the case of a simplified node distribution. Finally, we are interested on data collection mechanisms as they make inter-vehicle communications more efficient and reliable and minimize the bandwidth utilization. Our technique uses Q-learning to collect data among moving vehicles in VANETs. The aim behind using the learning technique is to make the collecting operation more reactive to nodes mobility and topology changes. For the simulation part, we compare it to a non-learning version to study the effect of the learning technique. Findings show that our technique far outperforms other propositions and achieves a good trade off between delay and collection ratio. In conclusion, we believe that the different contributions presented in this Thesis will improve the efficiency of inter-vehicle communications in both dissemination and data collection directions. In addition, our mathematical contributions will enrich the literature in terms of constructing suitable models to evaluate broadcasting techniques in urban zones

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: iii ¿ 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.

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