Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

Modeling And Dynamic Resource Allocation For High Definition And Mobile Video Streams

Video streaming traffic has been surging in the last few years, which has resulted in an increase of its Internet traffic share on a daily basis. The importance of video streaming management has been emphasized with the advent of High Definition: HD) video streaming, as it requires by its nature more network resources. In this dissertation, we provide a better support for managing HD video traffic over both wireless and wired networks through several contributions. We present a simple, general and accurate video source model: Simplified Seasonal ARIMA Model: SAM). SAM is capable of capturing the statistical characteristics of video traces with less than 5% difference from their calculated optimal models. SAM is shown to be capable of modeling video traces encoded with MPEG-4 Part2, MPEG-4 Part10, and Scalable Video Codec: SVC) standards, using various encoding settings. We also provide a large and publicly-available collection of HD video traces along with their analyses results. These analyses include a full statistical analysis of HD videos, in addition to modeling, factor and cluster analyses. These results show that by using SAM, we can achieve up to 50% improvement in video traffic prediction accuracy. In addition, we developed several video tools, including an HD video traffic generator based on our model. Finally, to improve HD video streaming resource management, we present a SAM-based delay-guaranteed dynamic resource allocation: DRA) scheme that can provide up to 32.4% improvement in bandwidth utilization

Efficient Routing and Scheduling in Wireless Networks

The temporal and spatial variation in wireless channel conditions, node mobility make it challenging to design protocols for wireless networks. In this thesis, we design efficient routing and scheduling algorithms which adapt to changing network conditions caused by varying link quality or node mobility to improve user-level performance. We design and analyze routing protocols for static, mobile and heterogeneous wireless networks. We analyze the performance of opportunistic and cooperative forwarding in static mesh networks showing that opportunism outperforms cooperation; we identify interference as the main cause for mitigating the potential gains achievable with cooperative forwarding. For mobile networks, we quantitatively analyze the tradeoff between state information collection (sampling frequency and number of bits per sample) and power consumption for a fixed source-to-destination goodput constraint. For heterogeneous networks comprising of both static and mobile nodes, we propose a greedy algorithm (adaptive-flood) which dynamically classifies individual nodes as routers/flooders depending on network conditions and demonstrate that it achieves performance equivalent to, and in some cases significantly better than, that of network-wide routing or flooding alone. Last, we consider an application-level wireless streaming scenario where multiple clients are streaming different videos from a cellular base station. We design a greedy algorithm for efficiently scheduling multiple video streams from a base station to mobile clients so as to minimize the total number of application-playout stalls. We develop models for coarse timescale wireless channel variation to aid network and application-layer protocol design

Video traffic : characterization, modelling and transmission

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A review of connection admission control algorithms for ATM networks

The emergence of high-speed networks such as those with ATM integrates large numbers of services with a wide range of characteristics. Admission control is a prime instrument for controlling congestion in the network. As part of connection services to an ATM system, the Connection Admission Control (CAC) algorithm decides if another call or connection can be admitted to the Broadband Network. The main task of the CAC is to ensure that the broadband resources will not saturate or overflow within a very small probability. It limits the connections and guarantees Quality of Service for the new connection. The algorithm for connection admission is crucial in determining bandwidth utilisation efficiency. With statistical multiplexing more calls can be allocated on a network link, while still maintaining the Quality of Service specified by the connection with traffic parameters and type of service. A number of algorithms for admission control for Broadband Services with ATM Networks are described and compared for performance under different traffic loads. There is a general description of the ATM Network as an introduction. Issues to do with source distributions and traffic models are explored in Chapter 2. Chapter 3 provides an extensive presentation of the CAC algorithms for ATM Broadband Networks. The ideas about the Effective Bandwidth are reviewed in Chapter 4, and a different approach to admission control using online measurement is presented in Chapter 5. Chapter 6 has the numerical evaluation of four of the key algorithms, with simulations. Finally Chapter 7 has conclusions of the findings and explores some possibilities for further work

Resource management in in-home digital networks using Dantzig-Wolfe decomposition

In een digitaal huisnetwerk zijn in het huis de verschillende digitale consumentenelektronica apparaten met elkaar verbonden, zoals een set-top-box, tv-scherm of harde schijf. Dit maakt nieuwe applicaties mogelijk, zoals het kunnen bekijken van een film op elke mogelijke plek in huis op elk gewenst moment zonder dat men precies weet waar deze film is opgeslagen. Deze nieuwe applicaties leiden echter tot nieuwe `resource management' problemen met als doel de `resources',zoals processoren, opslagapparatuur en communicatieverbindingen, zo efficient en effectief mogelijk te gebruiken.In dit proefschrift beschouwen we een enkele bus (communicatieverbinding) met beperkte bandbreedte, waarmee meerdere apparaten zijn verbonden. Tussen elk apparaat en de bus bevindt zich een buffer met beperkte capaciteit. Verder is er een verzameling video stromen gegeven waarbij elke stroom over de bus van het verzendend apparaat naar het ontvangend apparaat verzonden moet worden. Hierbij willen we voor iedere stroom een vast deel van de bandbreedte en betreffende buffers reserveren. We maken onderscheid tussen twee type stromen, te weten volledig gespecificeerde stromen en `leaky bucket' gereguleerde stromen. Van een volledig gespecificeerde stroom weten we exact hoeveel data er wanneer wordt aangeboden en gevraagd bij de buffers van zijn verzendend respectievelijk ontvangend apparaat. Van een `leaky bucket' gereguleerde stroom kennen we alleen de parameters van de `leaky buckets' die de data-aanvoer van de stroom reguleren.Met deze parameters kunnen we een bovengrens voor de data-aanvoer gedurende elk mogelijk tijdsinterval geven.Allereerst definieren wij het Multiple Streams Smoothing Problem (MSSP). In een instantie van MSSP is een verzameling volledig gespecificeerde stromengegeven, de bandbreedte van de bus en de groottes van de verschillende buffers.Voor elke stroom moet een vast deel van de bandbreedte en de buffergroottes worden bepaald alsmede een verzendschema waarmee alle data voor de stroom op tijd kan worden verzonden. We modelleren MSSP als een lineair programmeringsprobleem en laten zien hoe Dantzig-Wolfe decompositie hierop kan worden toegepast. Dit leidt tot een hoofdprobleem en voor iedere stroom een subprobleem. Het subprobleem voor een stroom bestaat uit het minimaliseren van de kosten van de gereserveerde bandbreedte en buffergroottes, waarbij de kostencoefficienten volgen uit het geoptimaliseerde hoofdprobleem. Voor elke mogelijke combinatie van positievekostencoefficienten beschrijven we voor dit subprobleem een efficiente methode om een optimale oplossing te bepalen. Voor het minimaliseren van enkel de bandbreedte of enkel de buffergrootte van ´e´en van beide buffers passen wij hiervoor bestaande methoden aan. Voor het minimaliseren van beide buffergroottes laten we zien dat een optimale oplossing wordt verkregen door eerst de duurste buffer te minimaliseren en daarna de goedkoopste. Voor het afwegen van de bandbreedtetegen ´e´en buffergrootte beschrijven we een specifieke inruilmethode. Voor het afwegen van de bandbreedte tegen beide buffergroottes herleiden we het subprobleem eerst tot het vinden van het minimum van een stuksgewijs lineaire, convexe functie op de bandbreedte. Vervolgens beschrijven we twee efficente zoekmethoden om het minimum van deze functie met bijbehorende bandbreedte en buffergroottes te bepalen. Met behulp van experimentele resultaten geven we voor problemen van realistische grootte een indicatie van de rekentijd en van de benuttingsgraad van de bepaalde bandbreedte- en bufferreserveringen.Voor de `leaky bucket' gereguleerde stromen definieren wij het MultipleLeaky-Bucket Streams Smoothing Problem (MLBSSP). In een instantie van MLBSSP is een verzameling `leaky bucket' gereguleerde stromen gegeven, waarvoor een vast deel van de bandbreedte en buffergroottes moet worden bepaald als medeverzendstrategien waarmee alle data op tijd kan worden verstuurd. Ook MLBSSP modelleren we als een lineair programmeringsprobleem. Verder tonen we aan dat MLBSSP te reduceren is tot MSSP door de bovengrens op de data-aanvoer als daadwerkelijke data-aanvoer te gebruiken voor iedere stroom. Deze bovengrens heeft een paar specifieke kenmerken, nl. concaviteit en stuksgewijs lineariteit, die we gebruiken om voor `leaky bucket' gereguleerde stromen de subproblemen nog efficienter op te lossen. Hiervoor leiden we vier nieuwe, noodzakelijke en voldoende voorwaarden voor de bandbreedte- en bufferreserveringen van een stroom af. Met behulp van deze voorwaarden is de tijd om een subprobleem op te lossen lineair afhankelijk van het aantal `leaky buckets' i.p.v. de lengte van een stroom,zoals voor volledig gespecificeerde stromen. Een oplossing kan nu binnen eenf ractie van een seconde bepaald worden. Om experimenten uit te voeren voor deze methode voor MLBSSP, genereren we verschillende `leaky bucket' beschrijvingen voor iedere volledig gespecificeerde stroom die gebruikt was in de resultaten voor MSSP. De resultaten van deze experimenten zijn voor stromen die zijn beschreven door hun maximale aantal benodigde `leaky buckets', gelijk aan de resultaten voor de volledig gespecificeerde stromen. Behalve de bovengenoemde `off-line' varianten van MSSP en MLBSSP beschouwen we ook `on-line' varianten van deze problemen. In de `on-line' varianten zijn de starttijden van stromen onbekend en zijn de kenmerken van een stroom pas bekend op het moment dat deze wil starten. Een oplossing voor een`on-line' variant kan worden bepaald door elke keer dat een nieuwe stroom start,de methode voor het `off-line' probleem te gebruiken om nieuwe bandbreedte- en bufferreserveringen te bepalen. Indien de reserveringen van bestaande stromen dan mogen worden aangepast, dient er bij het oplossen van de subproblemen voor deze stromen rekening gehouden te worden met de hoeveelheid data die er in totaal al verzonden is. Verdere toevoegingen aan de `off-line' methode die we beschouwen en die kunnen leiden tot een hoger aantal toegelaten stromen, zijn doelfuncties zoals het minimaliseren van de totale gereserveerde bandbreedte of buffergrootte van een specifieke buffer. Ook laten we zien hoe de maximale relatieve `resource' reservering geminimaliseerd kan worden. Tenslotte beschrijven we een aanpak voor de verzending van data van een stroom, waarbij data pas uit de buffers verwijderd wordt als dat nodig is om ruimte te maken voor nieuw aangeleverde data. Numerieke experimenten laten zien dat verschillende van deze aanpassingen inderdaad tot betere resultaten kunnen leiden. Het aantal toegelaten stromen in deze experimenten is voor een `on-line' variant met bepaalde toevoegingen net zo hoog als voor de `off-line' variant

Quality of service optimization of multimedia traffic in mobile networks

Mobile communication systems have continued to evolve beyond the currently deployed Third Generation (3G) systems with the main goal of providing higher capacity. Systems beyond 3G are expected to cater for a wide variety of services such as speech, data, image transmission, video, as well as multimedia services consisting of a combination of these. With the air interface being the bottleneck in mobile networks, recent enhancing technologies such as the High Speed Downlink Packet Access (HSDPA), incorporate major changes to the radio access segment of 3G Universal Mobile Telecommunications System (UMTS). HSDPA introduces new features such as fast link adaptation mechanisms, fast packet scheduling, and physical layer retransmissions in the base stations, necessitating buffering of data at the air interface which presents a bottleneck to end-to-end communication. Hence, in order to provide end-to-end Quality of Service (QoS) guarantees to multimedia services in wireless networks such as HSDPA, efficient buffer management schemes are required at the air interface. The main objective of this thesis is to propose and evaluate solutions that will address the QoS optimization of multimedia traffic at the radio link interface of HSDPA systems. In the thesis, a novel queuing system known as the Time-Space Priority (TSP) scheme is proposed for multimedia traffic QoS control. TSP provides customized preferential treatment to the constituent flows in the multimedia traffic to suit their diverse QoS requirements. With TSP queuing, the real-time component of the multimedia traffic, being delay sensitive and loss tolerant, is given transmission priority; while the non-real-time component, being loss sensitive and delay tolerant, enjoys space priority. Hence, based on the TSP queuing paradigm, new buffer managementalgorithms are designed for joint QoS control of the diverse components in a multimedia session of the same HSDPA user. In the thesis, a TSP based buffer management algorithm known as the Enhanced Time Space Priority (E-TSP) is proposed for HSDPA. E-TSP incorporates flow control mechanisms to mitigate congestion in the air interface buffer of a user with multimedia session comprising real-time and non-real-time flows. Thus, E-TSP is designed to provide efficient network and radio resource utilization to improve end-to-end multimedia traffic performance. In order to allow real-time optimization of the QoS control between the real-time and non-real-time flows of the HSDPA multimedia session, another TSP based buffer management algorithm known as the Dynamic Time Space Priority (D-TSP) is proposed. D-TSP incorporates dynamic priority switching between the real-time and non-real-time flows. D-TSP is designed to allow optimum QoS trade-off between the flows whilst still guaranteeing the stringent real-time component’s QoS requirements. The thesis presents results of extensive performance studies undertaken via analytical modelling and dynamic network-level HSDPA simulations demonstrating the effectiveness of the proposed TSP queuing system and the TSP based buffer management schemes

A study of self-similar traffic generation for ATM networks

This thesis discusses the efficient and accurate generation of self-similar traffic for ATM networks. ATM networks have been developed to carry multiple service categories. Since the traffic on a number of existing networks is bursty, much research focuses on how to capture the characteristics of traffic to reduce the impact of burstiness. Conventional traffic models do not represent the characteristics of burstiness well, but self-similar traffic models provide a closer approximation. Self-similar traffic models have two fundamental properties, long-range dependence and infinite variance, which have been found in a large number of measurements of real traffic. Therefore, generation of self-similar traffic is vital for the accurate simulation of ATM networks. The main starting point for self-similar traffic generation is the production of fractional Brownian motion (FBM) or fractional Gaussian noise (FGN). In this thesis six algorithms are brought together so that their efficiency and accuracy can be assessed. It is shown that the discrete FGN (dPGN) algorithm and the Weierstrass-Mandelbrot (WM) function are the best in terms of accuracy while the random midpoint displacement (RMD) algorithm, successive random addition (SRA) algorithm, and the WM function are superior in terms of efficiency. Three hybrid approaches are suggested to overcome the inefficiency or inaccuracy of the six algorithms. The combination of the dFGN and RMD algorithm was found to be the best in that it can generate accurate samples efficiently and on-the-fly. After generating FBM sample traces, a further transformation needs to be conducted with either the marginal distribution model or the storage model to produce self-similar traffic. The storage model is a better transformation because it provides a more rigorous mathematical derivation and interpretation of physical meaning. The suitability of using selected Hurst estimators, the rescaled adjusted range (R/S) statistic, the variance-time (VT) plot, and Whittle's approximate maximum likelihood estimator (MLE), is also covered. Whittle's MLE is the better estimator, the R/S statistic can only be used as a reference, and the VT plot might misrepresent the actual Hurst value. An improved method for the generation of self-similar traces and their conversion to traffic has been proposed. This, combined with the identification of reliable methods for the estimators of the Hurst parameter, significantly advances the use of self-similar traffic models in ATM network simulation

ATM network impairment to video quality

Includes bibliographical reference

QoS framework for video streaming in home networks

In this thesis we present a new SNR scalable video coding scheme. An important advantage of the proposed scheme is that it requires just a standard video decoder for processing each layer. The quality of the delivered video depends on the allocation of bit rates to the base and enhancement layers. For a given total bit rate, the combination with a bigger base layer delivers higher quality. The absence of dependencies between frames in enhancement layers makes the system resilient to losses of arbitrary frames from an enhancement layer. Furthermore, that property can be used in a more controlled fashion. An important characteristic of any video streaming scheme is the ability to handle network bandwidth fluctuations. We made a streaming technique that observes the network conditions and based on the observations reconfigures the layer configuration in order to achieve the best possible quality. A change of the network conditions forces a change in the number of layers or the bit rate of these layers. Knowledge of the network conditions allows delivery of a video of higher quality by choosing an optimal layer configuration. When the network degrades, the amount of data transmitted per second is decreased by skipping frames from an enhancement layer on the sender side. The presented video coding scheme allows skipping any frame from an enhancement layer, thus enabling an efficient real-time control over transmission at the network level and fine-grained control over the decoding of video data. The methodology proposed is not MPEG-2 specific and can be applied to other coding standards. We made a terminal resource manager that enables trade-offs between quality and resource consumption due to the use of scalable video coding in combination with scalable video algorithms. The controller developed for the decoding process optimizes the perceived quality with respect to the CPU power available and the amount of input data. The controller does not depend on the type of scalability technique and can therefore be used with any scalable video. The controller uses the strategy that is created offline by means of a Markov Decision Process. During the evaluation it was found that the correctness of the controller behavior depends on the correctness of parameter settings for MDP, so user tests should be employed to find the optimal settings