Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

QoS provisioning in multimedia streaming

Multimedia consists of voice, video, and data. Sample applications include video conferencing, video on demand, distance learning, distributed games, and movies on demand. Providing Quality of Service (QoS) for multimedia streaming has been a difficult and challenging problem. When multimedia traffic is transported over a network, video traffic, though usually compressed/encoded for bandwidth reduction, still consumes most of the bandwidth. In addition, compressed video streams typically exhibit highly variable bit rates as well as long range dependence properties, thus exacerbating the challenge in meeting the stringent QoS requirements of multimedia streaming with high network utilization. Dynamic bandwidth allocation in which video traffic prediction can play an important role is thus needed. Prediction of the variation of the I frame size using Least Mean Square (LMS) is first proposed. Owing to a smoother sequence, better prediction has been achieved as compared to the composite MPEG video traffic prediction scheme. One problem with this LMS algorithm is its slow convergence. In Variable Bit Rate (VBR) videos characterized by frequent scene changes, the LMS algorithm may result in an extended period of intractability, and thus may experience excessive cell loss during scene changes. A fast convergent non-linear predictor called Variable Step-size Algorithm (VSA) is subsequently proposed to overcome this drawback. The VSA algorithm not only incurs small prediction errors but more importantly achieves fast convergence. It tracks scene changes better than LMS. Bandwidth is then assigned based on the predicted I frame size which is usually the largest in a Group of Picture (GOP). Hence, the Cell Loss Ratio (CLR) can be kept small. By reserving bandwidth at least equal to the predicted one, only prediction errors need to be buffered. Since the prediction error was demonstrated to resemble white noise or exhibits at most short term memory, smaller buffers, less delay, and higher bandwidth utilization can be achieved. In order to further improve network bandwidth utilization, a QoS guaranteed on-line bandwidth allocation is proposed. This method allocates the bandwidth based on the predicted GOP and required QoS. Simulations and analytical results demonstrate that this scheme provides guaranteed delay and achieves higher bandwidth utilization. Network traffic is generally accepted to be self similar. Aggregating self similar traffic can actually intensify rather than diminish burstiness. Thus, traffic prediction plays an important role in network management. Least Mean Kurtosis (LMK), which uses the negated kurtosis of the error signal as the cost function, is proposed to predict the self similar traffic. Simulation results show that the prediction performance is improved greatly as compared to the LMS algorithm. Thus, it can be used to effectively predict the real time network traffic. The Differentiated Service (DiffServ) model is a less complex and more scalable solution for providing QoS to IP as compared to the Integrated Service (IntServ) model. We propose to transport MPEG frames through various service classes of DiffServ according to the MPEG video characteristics. Performance analysis and simulation results show that our proposed approach can not only guarantee QoS but can also achieve high bandwidth utilization. As the end video quality is determined not only by the network QoS but also by the encoded video quality, we consider video quality from these two aspects and further propose to transport spatial scalable encoded videos over DiffServ. Performance analysis and simulation results show that this can provision QoS guarantees. The dropping policy we propose at the egress router can reduce the traffic load as well as the risk of congestion in other domains

Towards a new generation of transport services adapted to multimedia application

Une connexion d'ordre et de fiabilité partiels (POC, partial order connection) est une connexion de transport autorisée à perdre certains objets mais également à les délivrer dans un ordre éventuellement différent de celui d'émission. L'approche POC établit un lien conceptuel entre les protocoles sans connexion au mieux et les protocoles fiables avec connexion. Le concept de POC est motivé par le fait que dans les réseaux hétérogènes sans connexion tels qu'Internet, les paquets transmis sont susceptibles de se perdre et d'arriver en désordre, entraînant alors une réduction des performances des protocoles usuels. De plus, on montre qu'un protocole associé au transport d'un flux multimédia permet une réduction très sensible de l'utilisation des ressources de communication et de mémorisation ainsi qu'une diminution du temps de transit moyen. Dans cet article, une extension temporelle de POC, nommée TPOC (POC temporisé), est introduite. Elle constitue un cadre conceptuel permettant la prise en compte des exigences de qualité de service des applications multimédias réparties. Une architecture offrant un service TPOC est également introduite et évaluée dans le cadre du transport de vidéo MPEG. Il est ainsi démontré que les connexions POC comblent, non seulement le fossé conceptuel entre les protocoles sans connexion et avec connexion, mais aussi qu'ils surpassent les performances des ces derniers lorsque des données multimédias (telles que la vidéo MPEG) sont transportées

Video traffic modeling and delivery

Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

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

サービスレベルネゴシエーションに基づくワイヤレスネットワークのサービス提供スキーム

Tohoku University加藤寧課

Distributed multimedia systems

A distributed multimedia system (DMS) is an integrated communication, computing, and information system that enables the processing, management, delivery, and presentation of synchronized multimedia information with quality-of-service guarantees. Multimedia information may include discrete media data, such as text, data, and images, and continuous media data, such as video and audio. Such a system enhances human communications by exploiting both visual and aural senses and provides the ultimate flexibility in work and entertainment, allowing one to collaborate with remote participants, view movies on demand, access on-line digital libraries from the desktop, and so forth. In this paper, we present a technical survey of a DMS. We give an overview of distributed multimedia systems, examine the fundamental concept of digital media, identify the applications, and survey the important enabling technologies.published_or_final_versio

Using reinforcement learning for dynamic link sharing problems under signaling constraints

Cataloged from PDF version of article.In static link sharing system, users are assigned a fixed bandwidth share of the link capacity irrespective of whether these users are active or not. On the other hand, dynamic link sharing refers to the process of dynamically allocating bandwidth to each active user based on the instantaneous utilization of the link. As an example, dynamic link sharing combined with rate adaptation capability of multimedia applications provides a novel quality of service (QoS) framework for HFC and broadband wireless networks. Frequent adjustment of the allocated bandwidth in dynamic link sharing, yields a scalability issue in the form of a significant amount of message distribution and processing power (i.e. signaling) in the shared link system. On the other hand, if the rate of applications is adjusted once for the highest loaded traffic conditions, a significant amount of bandwidth may be wasted depending on the actual traffic load. There is then a need for an optimal dynamic link sharing system that takes into account the tradeoff between signaling scalability and bandwidth efficiency. In this work, we introduce a Markov decision framework for the dynamic link sharing system, when the desired signaling rate is imposed as a constraint. Reinforcement learning methodology is adopted for the solution of this Markov decision problem, and the results demonstrate that the proposed method provides better bandwidth efficiency without violating the signaling rate requirement compared to other heuristics.Çelik, NuriM.S

Decentralising resource management in operating systems

This dissertation explores operating system mechanisms to allow resource-aware applications to be involved in the process of managing resources under the premise that these applications (1) potentially have some (implicit) notion of their future resource demands and (2) can adapt their resource demands. The general idea is to provide feedback to resource-aware applications so that they can proactively participate in the management of resources. This approach has the benefit that resource management policies can be removed from central entities and the operating system has only to provide mechanism. Furthermore, in contrast to centralised approaches, application specific features can be more easily exploited. To achieve this aim, I propose to deploy a microeconomic theory, namely congestion or shadow pricing, which has recently received attention for managing congestion in communication networks. Applications are charged based on the potential "damage" they cause to other consumers by using resources. Consumers interpret these congestion charges as feedback signals which they use to adjust their resource consumption. It can be shown theoretically that such a system with consumers merely acting in their own self-interest will converge to a social optimum. This dissertation focuses on the operating system mechanisms required to decentralise resource management this way. In particular it identifies four mechanisms: pricing & charging, credit accounting, resource usage accounting, and multiplexing. While the latter two are mechanisms generally required for the accurate management of resources, pricing & charging and credit accounting present novel mechanisms. It is argued that congestion prices are the correct economic model in this context and provide appropriate feedback to applications. The credit accounting mechanism is necessary to ensure the overall stability of the system by assigning value to credits

Quality of Service optimisation framework for Next Generation Networks

Within recent years, the concept of Next Generation Networks (NGN) has become widely accepted within the telecommunication area, in parallel with the migration of telecommunication networks from traditional circuit-switched technologies such as ISDN (Integrated Services Digital Network) towards packet-switched NGN. In this context, SIP (Session Initiation Protocol), originally developed for Internet use only, has emerged as the major signalling protocol for multimedia sessions in IP (Internet Protocol) based NGN. One of the traditional limitations of IP when faced with the challenges of real-time communications is the lack of quality support at the network layer. In line with NGN specification work, international standardisation bodies have defined a sophisticated QoS (Quality of Service) architecture for NGN, controlling IP transport resources and conventional IP QoS mechanisms through centralised higher layer network elements via cross-layer signalling. Being able to centrally control QoS conditions for any media session in NGN without the imperative of a cross-layer approach would result in a feasible and less complex NGN architecture. Especially the demand for additional network elements would be decreased, resulting in the reduction of system and operational costs in both, service and transport infrastructure. This thesis proposes a novel framework for QoS optimisation for media sessions in SIP-based NGN without the need for cross-layer signalling. One key contribution of the framework is the approach to identify and logically group media sessions that encounter similar QoS conditions, which is performed by applying pattern recognition and clustering techniques. Based on this novel methodology, the framework provides functions and mechanisms for comprehensive resource-saving QoS estimation, adaptation of QoS conditions, and support of Call Admission Control. The framework can be integrated with any arbitrary SIP-IP-based real-time communication infrastructure, since it does not require access to any particular QoS control or monitoring functionalities provided within the IP transport network. The proposed framework concept has been deployed and validated in a prototypical simulation environment. Simulation results show MOS (Mean Opinion Score) improvement rates between 53 and 66 percent without any active control of transport network resources. Overall, the proposed framework comes as an effective concept for central controlled QoS optimisation in NGN without the need for cross-layer signalling. As such, by either being run stand-alone or combined with conventional QoS control mechanisms, the framework provides a comprehensive basis for both the reduction of complexity and mitigation of issues coming along with QoS provision in NGN