13 research outputs found

    Meta-QoS performance of earliest-deadline-first and rate-monotonic scheduling of smoothed video data in a client-server environment

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    In this paper we present an extensive performance study of two modified EDF and RM scheduling algorithms which are enhanced to provide quality of service (QoS) guarantees for smoothed video data. With a probabilistic definition of QoS, we incorporate admission control conditions into the two algorithms. Furthermore, we also include a counter-based scheduling module as the core scheduling mechanism which adaptively adjusts the actual QoS levels assigned to requests. Our theoretical analysis of the two enhanced algorithms, called QEDF and QRM, shows that the QRM algorithm is more robust than the QEDF algorithm for different workload and utilization conditions. We also propose to use a new metric called meta-QoS to quantify the overall performance of a packet scheduler given a set of simultaneous requests. In our experiments, we find that the QRM algorithm can sustain a rather stable level of meta-QoS even when the workload and utilization levels are increased. On the other hand, the QEDF algorithm is found to be less desirable for a high level of utilization and a large number of requests.published_or_final_versio

    COMPARATIVE ANALYSIS OF NEURO- FUZZY AND SIMPLEX OPTIMIZATION MODEL FOR CONGESTION CONTROL IN ATM NETWORK.

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    Congestion always occurred when the transmission rate increased the data handling capacity of the network. Congestion normally arises when the network resources are not managed efficiently. Therefore if the source delivers at a speed higher then service rate queue, the queue size will be higher. Also if the queue size is finite, then the packet will observed delay. MATLAB Software was used to carry out simulations to develop Congestion control optimization Scheme for ATM Network with the aims to reducing the congestion of Enugu ATM Network. The results of the research reveal the minimization of congestion application model for Enugu ATM using optimization and Neuro-fuzzy. The result shows that congestion control model with Optimization and Neuro-fuzzy were 0.00003153 and 0.00002098 respectively. The ATM Congestion was reduced by 0.0000105, which is 18.2% decrease after Neuro-fuzzy controller was used. The results show the application of Neuro-fuzzy model which can use to control and minimized the ATM Congestion of Enugu ATM Network. The result shows that when Neuro-fuzzy is applied the congestion and the packet queue length in the buffer will be minimized. Key words: Congestion, MATLAB, Optimization, Neuro-fuzzy, ATM DOI: 10.7176/CTI/10-05 Publication date:July 31st 2020

    FAST Copper for Broadband Access

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    FAST Copper is a multi-year, U.S. NSF funded project that started in 2004, and is jointly pursued by the research groups of Mung Chiang at Princeton University, John Cioffi at Stanford University, and Alexander Fraser at Fraser Research Lab, and in collaboration with several industrial partners including AT&T. The goal of the FAST Copper Project is to provide ubiquitous, 100 Mbps, fiber/DSL broadband access to everyone in the US with a phone line. This goal will be achieved through two threads of research: dynamic and joint optimization of resources in Frequency, Amplitude, Space, and Time (thus the name 'FAST') to overcome the attenuation and crosstalk bottlenecks, and the integration of communication, networking, computation, modeling, and distributed information management and control for the multi-user twisted pair network

    Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC

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    abstract: Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC.View the article as published at https://www.hindawi.com/journals/tswj/2014/189481

    Video Smoothing of Aggregates of Streams with Bandwidth Constraints

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    Compressed variable bit rate (VBR) video transmission is acquiring a growing importance in the telecommunication world. High data rate variability of compressed video over multiple time scales makes an efficient bandwidth resource utilization difficult to obtain. One of the approaches developed to face this problem are smoothing techniques. Various smoothing algorithms that exploit client buffers have been proposed, thus reducing the peak rate and high rate variability by efficiently scheduling the video data to be transmitted over the network. The novel smoothing algorithm proposed in this paper, which represents a significant improvements over the existing methods, performs data scheduling both for a single stream and for stream aggregations, by taking into account available bandwidth constraints. It modifies, whenever possible, the smoothing schedule in such a way as to eliminate frame losses due to available bandwidth limitations. This technique can be applied to any smoothing algorithm already present in literature and can be usefully exploited to minimize losses in multiplexed stream scenarios, like Terrestrial Digital Video Broadcasting (DVB-T), where a specific known available bandwidth must be shared by several multimedia flows. The developed algorithm has been exploited for smoothing stored video, although it can also be quite easily adapted for real time smoothing. The obtained numerical results, compared with the MVBA, another smoothing algorithm that is already presented and discussed in literature, show the effectiveness of the proposed algorithm, in terms of lost video frames, for different multiplexed scenarios

    Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC

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    Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC

    Continuous-Time Collaborative Prefetching of Continuous Media

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    The Role of Caching in Future Communication Systems and Networks

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    This paper has the following ambitious goal: to convince the reader that content caching is an exciting research topic for the future communication systems and networks. Caching has been studied for more than 40 years, and has recently received increased attention from industry and academia. Novel caching techniques promise to push the network performance to unprecedented limits, but also pose significant technical challenges. This tutorial provides a brief overview of existing caching solutions, discusses seminal papers that open new directions in caching, and presents the contributions of this special issue. We analyze the challenges that caching needs to address today, also considering an industry perspective, and identify bottleneck issues that must be resolved to unleash the full potential of this promising technique

    Smoothing, statistical multiplexing, and call admission control for stored video

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    VBR compressed video is known to exhibit significant, multiple-time-scale rate variability. A number of researchers have considered transmitting stored video from a server to a client using smoothing algorithms to reduce this rate variability. These algorithms exploit client buffering capabilities and determine a "smooth" rate transmission schedule, while ensuring that a client buffer neither overflows nor underflows. In this paper, we investigate how video smoothing impacts the statistical multiplexing gains available with such traffic and show that a significant amount of statistical multiplexing gain can be still be achieved. We then examine the implication of these results on network resource management and call admission control when transmitting smooth stored video using variable-bit-rate (VBR) service and statistical Quality-of-Service (QoS) guarantees. Specifically, we present a call admission control scheme based on a Chernoff bound method that uses a simple, novel tr..

    Video compression with complete information for pre-recorded sources

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    Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 123-130).by David Michael Baylon.Ph.D
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