Queueing systems with different types of renovation mechanism and thresholds as the mathematical models of active queue management mechanism

This article is devoted to some aspects of using the renovation mechanism (different types of renovation are considered, definitions and brief overview are also given) with one or several thresholds as the mathematical models of active queue management mechanisms. The attention is paid to the queuing systems in which a threshold mechanism with renovation is implemented. This mechanism allows to adjust the number of packets in the system by dropping (resetting) them from the queue depending on the ratio of a certain control parameter with specified thresholds at the moment of the end of service on the device (server) (in contrast to standard RED-like algorithms, when a possible drop of a packet occurs at the time of arrivals of next packets in the system). The models with one, two and three thresholds with different types of renovation are under consideration. It is worth noting that the thresholds determine not only from which place in the buffer the packets are dropped, but also to which the reset of packets occurs. For some of the models certain analytical and numerical results are obtained (the references are given), some of them are only under investigation, so only the mathematical model and current results may be considered. Some results of comparing classic RED algorithm with renovation mechanism are presented.Работа посвящена некоторым аспектам использования механизма обновления (различные варианты обновления рассмотрены, определения и краткий обзор представлены) с одним или несколькими порогами в качестве математических моделей механизмов активного управления очередями. Описаны системы массового обслуживания, в которых реализован механизм обновления с порогами, позволяющий управлять числом заявок в системе путем их сброса из накопителя в зависимости от значения некоторого управляющего параметра и пороговых значений. Сброс заявок из накопителя происходит в момент окончания обслуживания заявки на приборе, что отличает данный механизм сброса от RED-подобных алгоритмов, для которых сброс возможен в момент поступления в систему. Представлены модели с одним, двумя или тремя порогами. В этих моделях пороговые значения определяют не только место, с которого в накопителе начинается сброс заявок, но и до какой позиции заявки могут быть сброшены. Для некоторых из описываемых моделей уже получены аналитические и численные результаты (ссылки на работы представлены), но большая часть моделей находится в процессе изучения, поэтому представлены только описания и некоторые текущие данные. Приведены некоторые результаты сравнения классического алгоритма RED с механизмом обновления

Modeling and estimation techniques for understanding heterogeneous traffic behavior

The majority of current internet traffic is based on TCP. With the emergence of new applications, especially new multimedia applications, however, UDP-based traffic is expected to increase. Furthermore, multimedia applications have sparkled the development of protocols responding to congestion while behaving differently from TCP. As a result, network traffc is expected to become more and more diverse. The increasing link capacity further stimulates new applications utilizing higher bandwidths of future. Besides the traffic diversity, the network is also evolving around new technologies. These trends in the Internet motivate our research work. In this dissertation, modeling and estimation techniques of heterogeneous traffic at a router are presented. The idea of the presented techniques is that if the observed queue length and packet drop probability do not match the predictions from a model of responsive (TCP) traffic, then the error must come from non-responsive traffic; it can then be used for estimating the proportion of non-responsive traffic. The proposed scheme is based on the queue length history, packet drop history, expected TCP and queue dynamics. The effectiveness of the proposed techniques over a wide range of traffic scenarios is corroborated using NS-2 based simulations. Possible applications based on the estimation technique are discussed. The implementation of the estimation technique in the Linux kernel is presented in order to validate our estimation technique in a realistic network environment

Centralized Rate Allocation and Control in 802.11-based Wireless Mesh Networks

Wireless Mesh Networks (WMNs) built with commodity 802.11 radios are a cost-effective means of providing last mile broadband Internet access. Their multihop architecture allows for rapid deployment and organic growth of these networks. 802.11 radios are an important building block in WMNs. These low cost radios are readily available, and can be used globally in license-exempt frequency bands. However, the 802.11 Distributed Coordination Function (DCF) medium access mechanism does not scale well in large multihop networks. This produces suboptimal behavior in many transport protocols, including TCP, the dominant transport protocol in the Internet. In particular, cross-layer interaction between DCF and TCP results in flow level unfairness, including starvation, with backlogged traffic sources. Solutions found in the literature propose distributed source rate control algorithms to alleviate this problem. However, this requires MAC-layer or transport-layer changes on all mesh routers. This is often infeasible in practical deployments. In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We evaluate the feasibility of establishing similar centralized control via gateway mesh routers in WMNs. We find that commonly used router-assisted flow control schemes designed for wired networks fail in WMNs. This is because they assume that: (1) links can be scheduled independently, and (2) router queue buildups are sufficient for detecting congestion. These abstractions do not hold in a wireless network, rendering wired scheduling algorithms such as Fair Queueing (and its variants) and Active Queue Management (AQM) techniques ineffective as a gateway-enforceable solution in a WMN. We show that only non-work-conserving rate-based scheduling can effectively enforce rate allocation via a single centralized traffic-aggregation point. In this context we propose, design, and evaluate a framework of centralized, measurement-based, feedback-driven mechanisms that can enforce a rate allocation policy objective for adaptive traffic streams in a WMN. In this dissertation we focus on fair rate allocation requirements. Our approach does not require any changes to individual mesh routers. Further, it uses existing data traffic as capacity probes, thus incurring a zero control traffic overhead. We propose two mechanisms based on this approach: aggregate rate control (ARC) and per-flow rate control (PFRC). ARC limits the aggregate capacity of a network to the sum of fair rates for a given set of flows. We show that the resulting rate allocation achieved by DCF is approximately max-min fair. PFRC allows us to exercise finer-grained control over the rate allocation process. We show how it can be used to achieve weighted flow rate fairness. We evaluate the performance of these mechanisms using simulations as well as implementation on a multihop wireless testbed. Our comparative analysis show that our mechanisms improve fairness indices by a factor of 2 to 3 when compared with networks without any rate limiting, and are approximately equivalent to results achieved with distributed source rate limiting mechanisms that require software modifications on all mesh routers

Improving video streaming experience through network measurements and analysis

Multimedia traffic dominates today’s Internet. In particular, the most prevalent traffic carried over wired and wireless networks is video. Most popular streaming providers (e.g. Netflix, Youtube) utilise HTTP adaptive streaming (HAS) for video content delivery to end-users. The power of HAS lies in the ability to change video quality in real time depending on the current state of the network (i.e. available network resources). The main goal of HAS algorithms is to maximise video quality while minimising re-buffering events and switching between different qualities. However, these requirements are opposite in nature, so striking a perfect blend is challenging, as there is no single widely accepted metric that captures user experience based on the aforementioned requirements. In recent years, researchers have put a lot of effort into designing subjectively validated metrics that can be used to map quality, re-buffering and switching behaviour of HAS players to the overall user experience (i.e. video QoE). This thesis demonstrates how data analysis can contribute in improving video QoE. One of the main characteristics of mobile networks is frequent throughput fluctuations. There are various underlying factors that contribute to this behaviour, including rapid changes in the radio channel conditions, system load and interaction between feedback loops at the different time scales. These fluctuations highlight the challenge to achieve a high video user experience. In this thesis, we tackle this issue by exploring the possibility of throughput prediction in cellular networks. The need for better throughput prediction comes from data-based evidence that standard throughput estimation techniques (e.g. exponential moving average) exhibit low prediction accuracy. Cellular networks deploy opportunistic exponential scheduling algorithms (i.e. proportional-fair) for resource allocation among mobile users/devices. These algorithms take into account a user’s physical layer information together with throughput demand. While the algorithm itself is proprietary to the manufacturer, physical layer and throughput information are exchanged between devices and base stations. Availability of this information allows for a data-driven approach for throughput prediction. This thesis utilises a machine-learning approach to predict available throughput based on measurements in the near past. As a result, a prediction accuracy with an error less than 15% in 90% of samples is achieved. Adding information from other devices served by the same base station (network-based information) further improves accuracy while lessening the need for a large history (i.e. how far to look into the past). Finally, the throughput prediction technique is incorporated to state-of-the-art HAS algorithms. The approach is validated in a commercial cellular network and on a stock mobile device. As a result, better throughput prediction helps in improving user experience up to 33%, while minimising re-buffering events by up to 85%. In contrast to wireless networks, channel characteristics of the wired medium are more stable, resulting in less prominent throughput variations. However, all traffic traverses through network queues (i.e. a router or switch), unlike in cellular networks where each user gets a dedicated queue at the base station. Furthermore, network operators usually deploy a simple first-in-first-out queuing discipline at queues. As a result, traffic can experience excessive delays due to the large queue sizes, usually deployed in order to minimise packet loss and maximise throughput. This effect, also known as bufferbloat, negatively impacts delay-sensitive applications, such as web browsing and voice. While there exist guidelines for modelling queue size, there is no work analysing its impact on video streaming traffic generated by multiple users. To answer this question, the performance of multiple videos clients sharing a bottleneck link is analysed. Moreover, the analysis is extended to a realistic case including heterogeneous round-trip-time (RTT) and traffic (i.e. web browsing). Based on experimental results, a simple two queue discipline is proposed for scheduling heterogeneous traffic by taking into account application characteristics. As a result, compared to the state-of-the-art Active Queue Management (AQM) discipline, Controlled Delay Management (CoDel), the proposed discipline decreases median Page Loading Time (PLT) of web traffic by up to 80% compared to CoDel, with no significant negative impact on video QoE

Quality of Service in Vehicular Ad Hoc Networks: Methodical Evaluation and Enhancements for ITS-G5

After many formative years, the ad hoc wireless communication between vehicles has become a vehicular technology available in mass production cars in 2020. Vehicles form spontaneous Vehicular Ad Hoc Networks (VANETs), which enable communication whenever vehicles are nearby without need for supportive infrastructure. In Europe, this communication is standardised comprehensively as Intelligent Transport Systems in the 5.9 GHz band (ITS-G5). This thesis centres around Quality of Service (QoS) in these VANETs based on ITS-G5 technology. Whilst only a few vehicles communicate, radio resources are plenty, and channel congestion is a minor issue. With progressing deployment, congestion control becomes crucial to preserve QoS by preventing high latencies or foiled information dissemination. The developed VANET simulation model, featuring an elaborated ITS-G5 protocol stack, allows investigation of QoS methodically. It also considers the characteristics of ITS-G5 radios such as the signal attenuation in vehicular environments and the capture effect by receivers. Backed by this simulation model, several enhancements for ITS-G5 are proposed to control congestion reliably and thus ensure QoS for its applications. Modifications at the GeoNetworking (GN) protocol prevent massive packet occurrences in a short time and hence congestion. Glow Forwarding is introduced as GN extension to distribute delay-tolerant information. The revised Decentralized Congestion Control (DCC) cross-layer supports low-latency transmission of event-triggered, periodic and relayed packets. DCC triggers periodic services and manages a shared duty cycle budget dedicated to packet forwarding for this purpose. Evaluation in large-scale networks reveals that this enhanced ITS-G5 system can reliably reduce the information age of periodically sent messages. The forwarding budget virtually eliminates the starvation of multi-hop packets and still avoids congestion caused by excessive forwarding. The presented enhancements thus pave the way to scale up VANETs for wide-spread deployment and future applications