18 research outputs found

    Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link

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    Bluetooth's default automatic repeat request (ARQ) scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly) B-slices by inspection of packet headers without the need for encoder intervention.</jats:p

    A Comprehensive Analysis of Literature Reported Mac and Phy Enhancements of Zigbee and its Alliances

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    Wireless communication is one of the most required technologies by the common man. The strength of this technology is rigorously progressing towards several novel directions in establishing personal wireless networks mounted over on low power consuming systems. The cutting-edge communication technologies like bluetooth, WIFI and ZigBee significantly play a prime role to cater the basic needs of any individual. ZigBee is one such evolutionary technology steadily getting its popularity in establishing personal wireless networks which is built on small and low-power digital radios. Zigbee defines the physical and MAC layers built on IEEE standard. This paper presents a comprehensive survey of literature reported MAC and PHY enhancements of ZigBee and its contemporary technologies with respect to performance, power consumption, scheduling, resource management and timing and address binding. The work also discusses on the areas of ZigBee MAC and PHY towards their design for specific applications

    Dynamic bandwidth allocation in ATM networks

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    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

    Prediction of Quality of Experience for Video Streaming Using Raw QoS Parameters

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    Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global Internet traffic in the near future. Today user experience is becoming a reliable indicator for video service providers and telecommunication operators to convey overall end-to-end system functioning. Towards this, there is a profound need for an efficient Quality of Experience (QoE) monitoring and prediction. QoE is a subjective metric, which deals with user perception and can vary due to the user expectation and context. However, available QoE measurement techniques that adopt a full reference method are impractical in real-time transmission since they require the original video sequence to be available at the receiver’s end. QoE prediction, however, requires a firm understanding of those Quality of Service (QoS) factors that are the most influential on QoE. The main aim of this thesis work is the development of novel and efficient models for video quality prediction in a non-intrusive way and to demonstrate their application in QoE-enabled optimisation schemes for video delivery. In this thesis, the correlation between QoS and QoE is utilized to objectively estimate the QoE. For this, both objective and subjective methods were used to create datasets that represent the correlation between QoS parameters and measured QoE. Firstly, the impact of selected QoS parameters from both encoding and network levels on video QoE is investigated. The obtained QoS/QoE correlation is backed by thorough statistical analysis. Secondly, the development of two novel hybrid non-reference models for predicting video quality using fuzzy logic inference systems (FIS) as a learning-based technique. Finally, attention was move onto demonstrating two applications of the developed FIS prediction model to show how QoE is used to optimise video delivery

    Quality of Service Controlled Multimedia Transport Protocol

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    PhDThis research looks at the design of an open transport protocol that supports a range of services including multimedia over low data-rate networks. Low data-rate multimedia applications require a system that provides quality of service (QoS) assurance and flexibility. One promising field is the area of content-based coding. Content-based systems use an array of protocols to select the optimum set of coding algorithms. A content-based transport protocol integrates a content-based application to a transmission network. General transport protocols form a bottleneck in low data-rate multimedia communicationbsy limiting throughpuot r by not maintainingt iming requirementsT. his work presents an original model of a transport protocol that eliminates the bottleneck by introducing a flexible yet efficient algorithm that uses an open approach to flexibility and holistic architectureto promoteQ oS.T he flexibility andt ransparenccyo mesi n the form of a fixed syntaxt hat providesa seto f transportp rotocols emanticsT. he mediaQ oSi s maintained by defining a generic descriptor. Overall, the structure of the protocol is based on a single adaptablea lgorithm that supportsa pplication independencen, etwork independencea nd quality of service. The transportp rotocol was evaluatedth rougha set of assessmentos:f f-line; off-line for a specific application; and on-line for a specific application. Application contexts used MPEG-4 test material where the on-line assessmenuts eda modified MPEG-4 pl; yer. The performanceo f the QoSc ontrolledt ransportp rotocoli s often bettert hano thers chemews hen appropriateQ oS controlledm anagemenatl gorithmsa re selectedT. his is shownf irst for an off-line assessmenwt here the performancei s compared between the QoS controlled multiplexer,a n emulatedM PEG-4F lexMux multiplexers chemea, ndt he targetr equirements. The performanceis also shownt o be better in a real environmentw hen the QoS controlled multiplexeri s comparedw ith the real MPEG-4F lexMux scheme

    A review of connection admission control algorithms for ATM networks

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    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

    Analyse intelligente de la qualité d'expérience (QoE) dans les réseaux de diffusion de contenu web et mutimédia

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    Today user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end to end system functioning. Moreover, to compete for a prominent market share, different network operators and service providers should retain and increase the customers’ subscription. To fulfil these requirements they require an efficient Quality of Experience (QoE) monitoring and estimation. However, QoE is a subjective metric and its evaluation is expensive and time consuming since it requires human participation. Therefore, there is a need for an objective tool that can measure the QoE objectively with reasonable accuracy in real-Time. As a first contribution, we analyzed the impact of network conditions on Video on Demand (VoD) services. We also proposed an objective QoE estimation tool that uses fuzzy expert system to estimate QoE from network layer QoS parameters. As a second contribution, we analyzed the impact of MAC layer QoS parameters on VoD services over IEEE 802.11n wireless networks. We also proposed an objective QoE estimation tool that uses random neural network to estimate QoE from the MAC layer perspective. As our third contribution, we analyzed the effect of different adaption scenarios on QoE of adaptive bit rate streaming. We also developed a web based subjective test platform that can be easily integrated in a crowdsourcing platform for performing subjective tests. As our fourth contribution, we analyzed the impact of different web QoS parameters on web service QoE. We also proposed a novel machine learning algorithm i.e. fuzzy rough hybrid expert system for estimating web service QoE objectivelyDe nos jours, l’expérience de l'utilisateur appelé en anglais « User Experience » est devenue l’un des indicateurs les plus pertinents pour les fournisseurs de services ainsi que pour les opérateurs de télécommunication pour analyser le fonctionnement de bout en bout de leurs systèmes (du terminal client, en passant par le réseaux jusqu’à l’infrastructure des services etc.). De plus, afin d’entretenir leur part de marché et rester compétitif, les différents opérateurs de télécommunication et les fournisseurs de services doivent constamment conserver et accroître le nombre de souscription des clients. Pour répondre à ces exigences, ils doivent disposer de solutions efficaces de monitoring et d’estimation de la qualité d'expérience (QoE) afin d’évaluer la satisfaction de leur clients. Cependant, la QoE est une mesure qui reste subjective et son évaluation est coûteuse et fastidieuse car elle nécessite une forte participation humaine (appelé panel de d’évaluation). Par conséquent, la conception d’un outil qui peut mesurer objectivement cette qualité d'expérience avec une précision raisonnable et en temps réel est devenue un besoin primordial qui constitue un challenge intéressant à résoudre. Comme une première contribution, nous avons analysé l'impact du comportement d’un réseau sur la qualité des services de vidéo à la demande (VOD). Nous avons également proposé un outil d'estimation objective de la QoE qui utilise le système expert basé sur la logique floue pour évaluer la QoE à partir des paramètres de qualité de service de la couche réseau. Dans une deuxième contribution, nous avons analysé l'impact des paramètres QoS de couche MAC sur les services de VoD dans le cadre des réseaux sans fil IEEE 802.11n. Nous avons également proposé un outil d'estimation objective de la QoE qui utilise le réseau aléatoire de neurones pour estimer la QoE dans la perspective de la couche MAC. Pour notre troisième contribution, nous avons analysé l'effet de différents scénarios d'adaptation sur la QoE dans le cadre du streaming adaptatif au débit. Nous avons également développé une plate-Forme Web de test subjectif qui peut être facilement intégré dans une plate-Forme de crowd-Sourcing pour effectuer des tests subjectifs. Finalement, pour notre quatrième contribution, nous avons analysé l'impact des différents paramètres de qualité de service Web sur leur QoE. Nous avons également proposé un algorithme d'apprentissage automatique i.e. un système expert hybride rugueux basé sur la logique floue pour estimer objectivement la QoE des Web service

    Fuzzy Logic in Surveillance Big Video Data Analysis: Comprehensive Review, Challenges, and Research Directions

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    CCTV cameras installed for continuous surveillance generate enormous amounts of data daily, forging the term “Big Video Data” (BVD). The active practice of BVD includes intelligent surveillance and activity recognition, among other challenging tasks. To efficiently address these tasks, the computer vision research community has provided monitoring systems, activity recognition methods, and many other computationally complex solutions for the purposeful usage of BVD. Unfortunately, the limited capabilities of these methods, higher computational complexity, and stringent installation requirements hinder their practical implementation in real-world scenarios, which still demand human operators sitting in front of cameras to monitor activities or make actionable decisions based on BVD. The usage of human-like logic, known as fuzzy logic, has been employed emerging for various data science applications such as control systems, image processing, decision making, routing, and advanced safety-critical systems. This is due to its ability to handle various sources of real world domain and data uncertainties, generating easily adaptable and explainable data-based models. Fuzzy logic can be effectively used for surveillance as a complementary for huge-sized artificial intelligence models and tiresome training procedures. In this paper, we draw researchers’ attention towards the usage of fuzzy logic for surveillance in the context of BVD. We carry out a comprehensive literature survey of methods for vision sensory data analytics that resort to fuzzy logic concepts. Our overview highlights the advantages, downsides, and challenges in existing video analysis methods based on fuzzy logic for surveillance applications. We enumerate and discuss the datasets used by these methods, and finally provide an outlook towards future research directions derived from our critical assessment of the efforts invested so far in this exciting field

    Modeling network traffic on a global network-centric system with artificial neural networks

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    This dissertation proposes a new methodology for modeling and predicting network traffic. It features an adaptive architecture based on artificial neural networks and is especially suited for large-scale, global, network-centric systems. Accurate characterization and prediction of network traffic is essential for network resource sizing and real-time network traffic management. As networks continue to increase in size and complexity, the task has become increasingly difficult and current methodology is not sufficiently adaptable or scaleable. Current methods model network traffic with express mathematical equations which are not easily maintained or adjusted. The accuracy of these models is based on detailed characterization of the traffic stream which is measured at points along the network where the data is often subject to constant variation and rapid evolution. The main contribution of this dissertation is development of a methodology that allows utilization of artificial neural networks with increased capability for adaptation and scalability. Application on an operating global, broadband network, the Connexion by Boeingʼ network, was evaluated to establish feasibility. A simulation model was constructed and testing was conducted with operational scenarios to demonstrate applicability on the case study network and to evaluate improvements in accuracy over existing methods --Abstract, page iii
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