Optimization of TFRC loss history initialization

This letter deals with the initialization of the loss history structure in the TFRC (TCP-Friendly Rate Control) mechanism. This initialization occurs after the detection of the first loss event after every slowstart phase. The loss history is crucial for the algorithm since it returns the packet loss rate estimation. This estimation is used in the TFRC equation to compute the sending rate. In this letter, we propose a new method to compute the packet loss rate which is more computationally efficient and remains as accurate as the classical commonly used method. The motivation of this work is to reduce the computation time and formulate a unified computation scheme. This method is based on the Newton’s algorithm issued from numerical analysis of the TCP throughput equation. This proposal is evaluated analytically and the results show a significant improvement in terms of the computation time

Understanding the impact of TFRC feedbacks frequency over long delay links

TFRC is a transport protocol specifically designed to carry multimedia streams. TFRC does not enable a reliable and in order data delivery services. However the mechanism is designed to be friendly with TCP flows and thus, enables a control congestion algorithm. This congestion control relies in a feedback mechanism allowing receivers to communicate to the senders an experienced drop rate. Several studies attempted to adapt TFRC to a wide range of network conditions and topologies. Although the current TFRC RFC writes that there is little gain from sending a large number of feedback messages per RTT, recent studies have shown that in long-delay contexts, such as satellite-based networks, the performance of TFRC can be greatly improved by increasing the feedback frequency. Nevertheless, currently it is not clear how and why this increase may improve the performance of TFRC. Therefore, in this paper, we aim at understanding the impact that multiple feedback per RTT may have (i) on the key parameters of TFRC (RTT, drop rate, and sending rate) and (ii) on the network parameters (reactiveness and link utilization).We also provide a detailed description of the micro-mechanisms at the origin of the improvements of the TFRC behaviour when multiple feedback per RTT are delivered, and determine the context where such feedback frequencies should be applied

Toward a versatile transport protocol

Les travaux présentés dans cette thèse ont pour but d'améliorer la couche transport de l'architecture réseau de l'OSI. La couche transport est de nos jour dominée par l'utilisation de TCP et son contrôle de congestion. Récemment de nouveaux mécanismes de contrôle de congestion ont été proposés. Parmi eux TCP Friendly Rate Control (TFRC) semble être le plus abouti. Cependant, tout comme TCP, ce mécanisme ne prend pas en compte ni les évolutions du réseau ni les nouveaux besoins des applications. La première contribution de cette thèse consiste en une spécialisation de TFRC afin d'obtenir un protocole de transport avisé de la Qualité de Service (QdS) spécialement défini pour des réseaux à QdS offrant une garantie de bande passante. Ce protocole combine un mécanisme de contrôle de congestion orienté QdS qui prend en compte la réservation de bande passante au niveau réseau, avec un service de fiabilité totale afin de proposer un service similaire à TCP. Le résultat de cette composition constitue le premier protocole de transport adapté à des réseau à garantie de bande passante. En même temps que cette expansion de service au niveau réseau, de nouvelles technologies ont été proposées et déployées au niveau physique. Ces nouvelles technologies sont caractérisées par leur affranchissement de support filaire et la mobilité des systèmes terminaux. De plus, elles sont généralement déployées sur des entités où la puissance de calcul et la disponibilité mémoire sont inférieures à celles des ordinateurs personnels. La deuxième contribution de cette thèse est la proposition d'une adaptation de TFRC à ces entités via la proposition d'une version allégée du récepteur. Cette version a été implémentée, évaluée quantitativement et ses nombreux avantages et contributions ont été démontrés par rapport à TFRC. Enfin, nous proposons une optimisation des implémentations actuelles de TFRC. Cette optimisation propose tout d'abord un nouvel algorithme pour l'initialisation du récepteur basé sur l'utilisation de l'algorithme de Newton. Nous proposons aussi l'introduction d'un outil nous permettant d'étudier plus en détails la manière dont est calculé le taux de perte du côté récepteur. ABSTRACT : This thesis presents three main contributions that aim to improve the transport layer of the current networking architecture. The transport layer is nowadays overruled by the use of TCP and its congestion control. Recently new congestion control mechanisms have been proposed. Among them, TCP Friendly Rate Control (TFRC) appears to be one of the most complete. Nevertheless this congestion control mechanism, as TCP, does not take into account either the evolution of the network in terms of Quality of Service and mobility or the evolution of the applications. The first contribution of this thesis is a specialisation TFRC congestion control to propose a QoS-aware Transport Protocol specifically designed to operate over QoS-enabled networks with bandwidth guarantee mechanisms. This protocol combines a QoS-aware congestion control, which takes into account networklevel bandwidth reservations, with full reliability in order mechanism to provide a transport service similar to TCP. As a result, we obtain the guaranteed throughput at the application level where TCP fails. This protocol is the first transport protocol compliant with bandwidth guaranteed networks. At the same time the set of network services expands, new technologies have been proposed and deployed at the physical layer. These new technologies are mainly characterised by communications done without wire constraint and the mobility of the end-systems. Furthermore, these technologies are usually deployed on entities where the CPU power and memory storage are limited. The second contribution of this thesis is therefore to propose an adaptation of TFRC to these entities. This is accomplished with the proposition of a new sender-based version of TFRC. This version has been implemented, evaluated and its numerous contributions and advantages compare to usual TFRC version have been demonstrated. Finally, we proposed an optimisation of actual implementations of TFRC. This optimisation first consists in the proposition of an algorithm based on a numerical analysis of the equation used in TFRC and the use of the Newton's algorithm. We furthermore give a first step, with the introduction of a new framework for TFRC, in order to better understand TFRC behaviour and to optimise the computation of the packet loss rate according to loss probability distribution

Adapting End Host Congestion Control for Mobility

Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP

Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems

Congestion control for real-time interactive multimedia streams

The Internet is getting richer, and so the services. The richer the services, the more the users demand. The more they demand, the more we guarantee(1). This thesis investigates the congestion control mechanisms for interactive multimedia streaming applications. We start by raising a question as to why the congestion control schemes are not widely deployed in real-world applications, and study what options are available at present. We then discuss and show some of the good reasonings that might have made the control mechanism, specifically speaking the rate-based congestion control mechanism, not so attractive. In an effort to address the problems, we identify the existing problems from which the rate-based congestion control protocol cannot easily escape. We therefore propose a simple but novel windowbased congestion control protocol that can retain smooth throughput property while being fair when competing with TCP, yet still being responsive to the network changes. Through the extensive ns-2 simulations and the real-world experiments, we evaluate TFWC, our proposed mechanisms, and TFRC, the proposed IETF standard, in terms of network-oriented metrics (fairness, smoothness, stability, and responsive), and end-user oriented metrics (PSNR and MOS) to throughly study the protocol’s behaviors. We then discuss and conclude the options of the evaluated protocols for the real application. (1)We as congestion control mechanisms in the Internet

Detecting Biomarkers among Subgroups with Structured Latent Features and Multitask Learning Methods

University of Minnesota Ph.D. dissertation. May 2017. Major: Computer Science. Advisor: Rui Kuang. 1 computer file (PDF); viii, 89 pages.Because of disease progression and heterogeneity in samples and single cells, biomarker detection among subgroups is important as it provides better understanding on population genetics and cancer causative. In this thesis, we proposed several structured latent features based and multitask learning based methods for biomarker detection on DNA Copy-Number Variations (CNVs) data and single cell RNA sequencing (scRNA-seq) data. By incorporating prior known group information or taking domain heterogeneity into consideration, our models are able to achieve meaningful biomarker detection and accurate sample classification. 1. By cooperating population relationship from human phylogenetic tree, we introduced a latent feature model to detect population-differentiation CNV markers. The algorithm, named tree-guided sparse group selection (treeSGS), detects sample sub- groups organized by a population phylogenetic tree such that the evolutionary relations among the populations are incorporated for more accurate detection of population- differentiation CNVs. 2. We applied transfer learning technic for cross-cancer-type CNV studies. We proposed Transfer Learning with Fused LASSO (TLFL) algorithm, which detects latent CNV components from multiple CNV datasets of different tumor types and distinguishes the CNVs that are common across the datasets and those that are specific in each dataset. Both the common and type-specific CNVs are detected as latent components in matrix factorization coupled with fused LASSO on adjacent CNV probe features. 3. We further applied multitask learning idea on scRNA-seq data. We introduced variance-driven multitask clustering on single-cell RNA-seq data (scV DMC) that utilizes multiple cell populations from biological replicates or related samples with significant biological variances. scVDMC clusters single cells of similar cell types and markers but varies expression patterns across different domains such that the scRNA-seq data are adjusted for better integration. We applied both simulations and several publicly available CNV and scRNA-seq datasets, including one in house scRNA-seq dataset, to evaluate the performance of our models. The promising results show that we achieve better biomarker prediction among subgroups

Real-time data flow models and congestion management for wire and wireless IP networks

Includes abstract.Includes bibliographical references (leaves 103-111).In video streaming, network congestion compromises the video throughput performance and impairs its perceptual quality and may interrupt the display. Congestion control may take the form of rate adjustment through mechanisms by attempt to minimize the probability of congestion by adjusting the rate of the streaming video to match the available capacity of the network. This can be achieved either by adapting the quantization parameter of the video encoder or by varying the rate through a scalable video technique. This thesis proposes a congestion control protocol for streaming video where an interaction between the video source and the receiver is essential to monitor the network state. The protocol consists of adjusting the video transmission rate at the encoder whenever a change in the network conditions is observed and reported back to the sender