Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems

QoS in IEEE 802.11-based Wireless Networks: A Contemporary Survey

Apart from mobile cellular networks, IEEE 802.11-based wireless local area networks (WLANs) represent the most widely deployed wireless networking technology. With the migration of critical applications onto data networks, and the emergence of multimedia applications such as digital audio/video and multimedia games, the success of IEEE 802.11 depends critically on its ability to provide quality of service (QoS). A lot of research has focused on equipping IEEE 802.11 WLANs with features to support QoS. In this survey, we provide an overview of these techniques. We discuss the QoS features incorporated by the IEEE 802.11 standard at both physical (PHY) and media access control (MAC) layers, as well as other higher-layer proposals. We also focus on how the new architectural developments of software-defined networking (SDN) and cloud networking can be used to facilitate QoS provisioning in IEEE 802.11-based networks. We conclude this paper by identifying some open research issues for future consideration

Link Adaptation for Wireless Video Communication Systems

This PhD thesis considers the performance evaluation and enhancement of video communication over wireless channels. The system model considers hybrid automatic repeat request (HARQ) with Chase combining and turbo product codes (TPC). The thesis proposes algorithms and techniques to optimize the throughput, transmission power and complexity of HARQ-based wireless video communication. A semi-analytical solution is developed to model the performance of delay-constrained HARQ systems. The semi-analytical and Monte Carlo simulation results reveal that significant complexity reduction can be achieved by noting that the coding gain advantage of the soft over hard decoding is reduced when Chase combining is used, and it actually vanishes completely for particular codes. Moreover, the thesis proposes a novel power optimization algorithm that achieves a significant power saving of up to 80%. Joint throughput maximization and complexity reduction is considered as well. A CRC (cyclic redundancy check)-free HARQ is proposed to improve the system throughput when short packets are transmitted. In addition, the computational complexity/delay is reduced when the packets transmitted are long. Finally, a content-aware and occupancy-based HARQ scheme is proposed to ensure minimum video quality distortion with continuous playback.Comment: PhD Thesi

On-board B-ISDN fast packet switching architectures. Phase 1: Study

The broadband integrate services digital network (B-ISDN) is an emerging telecommunications technology that will meet most of the telecommunications networking needs in the mid-1990's to early next century. The satellite-based system is well positioned for providing B-ISDN service with its inherent capabilities of point-to-multipoint and broadcast transmission, virtually unlimited connectivity between any two points within a beam coverage, short deployment time of communications facility, flexible and dynamic reallocation of space segment capacity, and distance insensitive cost. On-board processing satellites, particularly in a multiple spot beam environment, will provide enhanced connectivity, better performance, optimized access and transmission link design, and lower user service cost. The following are described: the user and network aspects of broadband services; the current development status in broadband services; various satellite network architectures including system design issues; and various fast packet switch architectures and their detail designs

Space Shuttle/TDRSS communication and tracking systems analysis

In order to evaluate the technical and operational problem areas and provide a recommendation, the enhancements to the Tracking and Data Delay Satellite System (TDRSS) and Shuttle must be evaluated through simulation and analysis. These enhancement techniques must first be characterized, then modeled mathematically, and finally updated into LinCsim (analytical simulation package). The LinCsim package can then be used as an evaluation tool. Three areas of potential enhancements were identified: shuttle payload accommodations, TDRSS SSA and KSA services, and shuttle tracking system and navigation sensors. Recommendations for each area were discussed

Sequential Coding of Markov Sources over Burst Erasure Channels

We study sequential coding of Markov sources under an error propagation constraint. An encoder sequentially compresses a sequence of vector-sources that are spatially i.i.d. but temporally correlated according to a first-order Markov process. The channel erases up to B packets in a single burst, but reveals all other packets to the destination. The destination is required to reproduce all the source-vectors instantaneously and in a lossless manner, except those sequences that occur in an error propagation window of length B + W following the start of the erasure burst. We define the rate-recovery function R(B, W) - the minimum achievable compression rate per source sample in this framework - and develop upper and lower bounds on this function. Our upper bound is obtained using a random binning technique, whereas our lower bound is obtained by drawing connections to multi-terminal source coding. Our upper and lower bounds coincide, yielding R(B, W), in some special cases. More generally, both the upper and lower bounds equal the rate for predictive coding plus a term that decreases as 1/(W+1), thus establishing a scaling behaviour of the rate-recovery function. For a special class of semi-deterministic Markov sources we propose a new optimal coding scheme: prospicient coding. An extension of this coding technique to Gaussian sources is also developed. For the class of symmetric Markov sources and memoryless encoders, we establish the optimality of random binning. When the destination is required to reproduce each source sequence with a fixed delay and when W = 0 we also establish the optimality of binning.Comment: 22 pages, 12 figures, Submitted to IEEE Transaction on Information Theor

Techniques for broadband power line communications: impulsive noise mitigation and adaptive modulation

The development of power line communication systems for broadband multimedia applications requires a comprehensive knowledge of the channel characteristics and the main peculiarities that may influence the communication over this channel. PLC has the potential to become the preferred connectivity solution to homes and offices. Additionally, indoor power line networks can serve as local area networks offering high-speed data, audio, video and multimedia applications. The PLC technology eliminates the need for new wires by using an already-existing infrastructure that is much more pervasive than any other wired system. Power line networks, however, present a hostile channel for communication signals. Noise, multipath, selective fading and attenuation are well-known peculiarities of power line grids and. Particularly, random impulsive noise characterized with short durations and very high amplitudes is identified as one of the major impairments that degrade the performance of PLC systems. Orthogonal frequency division multiplexing (OFDM) is the technique of choice for broadband PLC systems. OFDM minimizes the effects of multipath and provides high robustness against selective fading. It is also powerful in impulsive noise environments and performs better than single-carrier modulation methods. If an OFDM symbol is affected by impulsive noise, the effect is spread over multiple subcarriers due to the discrete Fourier transform at the receiver. In order to achieve reliable outcomes, suitable channel and noise models must be used in the investigations. In this thesis, the power line channel transfer function is modelled using a multipath model that was proposed by Zimmermann and Dostert [1], [2]. This model describes the signal propagation scenario and attenuation effects in power line networks. To represent the actual noise scenario in power networks, the noise is classified into two main classes: background noise and impulsive noise. To reduce the effect of impulsive noise, conventional time domain nonlinearities are examined in this thesis under PLC environments. An adaptive-threshold selection method based on minimum bit-error rate (BER) is proposed. At the cost of additional complexity, the effect of impulsive noise is further mitigated using a novel joint time-domain/frequency-domain suppression technique. Since channel coding is essential for most telecommunication systems, we examine convolutional codes combined with interleaving in a PLC channel impaired with AWGN and impulsive noise. The results show substantial performance gains especially in heavily-disturbed environments, where signal-to-noise ratio (SNR) gains of more than 15 dB can be achieved with a code rate of 1/3. Bit-interleaved convolutionally-coded OFDM completely eliminates the effect of impulsive noise in weakly-disturbed noise environments, while a negligible effect may remain in medium-disturbed environments. A new power-loading algorithm that minimizes the transmission power for target BER and data rate constraints is introduced in later chapters of the thesis. Results indicate that the algorithm achieves performance gains of more than 4 dB SNR over conventional OFDM systems. Furthermore, a novel minimum-complexity bit-loading algorithm that maximizes the data rate given BER and power level constraints is proposed in chapter 6. Results show that this bit-loading algorithm achieves almost identical performance as the incremental algorithm but with much lower complexity

Improving Large-Scale Network Traffic Simulation with Multi-Resolution Models

Simulating a large-scale network like the Internet is a challenging undertaking because of the sheer volume of its traffic. Packet-oriented representation provides high-fidelity details but is computationally expensive; fluid-oriented representation offers high simulation efficiency at the price of losing packet-level details. Multi-resolution modeling techniques exploit the advantages of both representations by integrating them in the same simulation framework. This dissertation presents solutions to the problems regarding the efficiency, accuracy, and scalability of the traffic simulation models in this framework. The ``ripple effect\u27\u27 is a well-known problem inherent in event-driven fluid-oriented traffic simulation, causing explosion of fluid rate changes. Integrating multi-resolution traffic representations requires estimating arrival rates of packet-oriented traffic, calculating the queueing delay upon a packet arrival, and computing packet loss rate under buffer overflow. Real time simulation of a large or ultra-large network demands efficient background traffic simulation. The dissertation includes a rate smoothing technique that provably mitigates the ``ripple effect\u27\u27, an accurate and efficient approach that integrates traffic models at multiple abstraction levels, a sequential algorithm that achieves real time simulation of the coarse-grained traffic in a network with 3 tier-1 ISP (Internet Service Provider) backbones using an ordinary PC, and a highly scalable parallel algorithm that simulates network traffic at coarse time scales