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We consider end-to-end live video streaming in mobile edge networks with fluctuating but predictable throughput. We employ scalable video coding (SVC) to adapt the bitrate of each frame to the throughput evolution in a timely manner. When streaming SVC-encoded live video, the video source should dynamically derive and configure a set of coding parameters for each upcoming chunk, which consists of a number of consecutive frames. The coding parameters quantify the throughput evolution of an upcoming chunk by providing a few bitrate options for the frames within this chunk to encode with. Unlike the majority of existing works that simply treat the coding parameters as given (i.e., taking them for granted), in this paper, we derive the coding parameters from a comprehensive mathematical modeling and optimization perspective. Our approach consists of an optimization problem that captures the fundamental trade-off in determining the coding parameters and a customized search algorithm based on the analysis of the optimization problem's solution structure. Numerical results produced by the NS-3 network simulator show that our approach outperforms the state-of-the-art benchmarks. [ABSTRACT FROM AUTHOR]

This article investigates the reliability gain of broadcast (BC)/broadband (BB) cooperation for mobile scalable video streaming. A specific form of BC-BB cooperation is introduced, which is referred to as cooperative casting. The proposed system primarily utilizes a BC transmission for streaming, while BB backup transmissions are requested whenever the BC signal is not decodable. For BC deliveries in this system, a cross-layer collaboration between scalable video coding (SVC) and layered-division multiplexing is used to improve spectral efficiency by coupling their hierarchical structures. In this end, in tandem with designing the uplink requesting rules based on channel status, delivery performance of the cooperative casting is analytically evaluated in a probabilistic framework. The system design and analyses presented in this article focus on the service continuity in a mobile and time-varying channel, where the physical aspects, such as delayed unicast response and inter-carrier interference, are carefully taken into account. Compared to the standalone network transmissions, the cooperative casting is numerically verified to better prevent the delivery failures in high-speed mobile channels, especially when the SVC layer-combined (full-scale video) service is intended. Furthermore, it is also shown that relaxing the criteria for the BB stream requesting can reduce delivery failures substantially, while it increases transmission redundancy. [ABSTRACT FROM AUTHOR]

Aided by scalable video coding, multirate multicast has become a promising technique of providing differentiated quality of experience (QoE) for massive numbers of video subscribers operating in heterogeneous channel conditions. Nevertheless, due to the time-varying nature of wireless channels and the subscribers’ diverse requirements, it is challenging to dynamically control the video rate in the light of the available radio resource to achieve the best QoE. To elaborate a little further, the time scale of resource scheduling is of short-term nature, which determines the short-term video quality variation, but from a service provider's perspective the design objective is to optimize the long-term QoE for all subscribers. Despite its importance, this problem has not been considered before. Explicitly, we formulated this problem as a time-averaged stochastic optimization problem which avoids the impact of both the short-term channel quality fluctuation and that of the video bitrates, whilst maintaining both inter- and intra- group fairness. The stratified structure of the problem inspires us to decompose it into a two-phase optimization: coarse grained assignment for each user group and fine grained assignment for each subgroup. We propose an adaptive multicast algorithm based on Lyapunov's optimization theory for solving this problem, by striking a compelling trade-off between the system's utility and its queue stability. We quantify the achievable performance of our proposed solution based on realistic video traces. [ABSTRACT FROM AUTHOR]

The problem of adaptive multi-user scalable layered video transmission is considered in energy harvesting (EH) aided wireless communication systems. With the goal of improving the quality of video services while providing fairness amongst the users despite the random nature of both energy harvesting and the channel quality, we formulate our Scalable Video Coding (SVC) design as a Constrained Utility Function Maximization (CUFM) problem. The proportional fairness and playback smoothness of our design is guaranteed by maximizing the log-sum of the users’ video qualities, while satisfying the battery fullness constraint and video layer (quality) fluctuation constraint. By invoking the classical Lyapunov drift based optimization technique, we further decompose the CUFM problem into two parallel subproblems, i.e., a dynamic transmission power allocation problem and a dynamic layer selection problem. By solving these two subproblems, we derive a joint power allocation and video layer selection strategy for multi-user SVC video transmission. The theoretical performance bound of the proposed solution is also presented. Numerical simulations are conducted with real H.264 SVC video traces and the experimental results demonstrate the reduced playback interruption rate and layer switching rate compared to a heuristic algorithm ProNTO. The results also illustrate a tradeoff between the system's utility function and the playback smoothness experienced by the users. [ABSTRACT FROM AUTHOR]

The use of high-quality 360° panoramic video is booming in the video industry. However, existing schemes for smartphones suffer from significant bandwidth consumption as they transmit the entire panoramic views in very high resolutions. This demand for bandwidth becomes even more problematic when multiple adjacent smartphones compete to access the same content, which further challenges a wireless network’s capacity, and when the available bandwidth fluctuates much more than wired networks. In this paper, we propose a cooperative streaming scheme for tile-based 360° video using scalable video coding (SVC) to maximize a group of users’ quality of experience. We formulate an optimization problem to choose optimal downloading and sharing subsets from a set of all requested SVC layers of tiles to maximize the effective quality of the users’ viewport while meeting the feasibility of the bandwidth of heterogeneous networks. We then show that the problem is NP-hard and compose a heuristic approach. In the approach, we rank the SVC layers based on the aggregated group-level preference to guide the devices’ downloading and sharing activities. A prototype on the Android platform is developed to test the approach’s performance, and the real-world results show that our proposed scheme outperforms baseline alternatives. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cooperative multi-user video streaming system, termed GiantClient, for videos encoded using scalable video coding (SVC). The proposed system allows a group of users to watch a video on a single screen. The users, who may have different data plans from different carriers or different levels of energy, can collaborate to fetch the SVC-encoded video at high quality and avoid running into re-buffering. Using SVC, each layer of every chunk of the video can be fetched by only one of the cooperating users. Therefore, we formulate the streaming problem that obtains the quality and the fetching policy decisions as an optimization problem. The objective is to optimize a novel quality-of-experience metric that maintains a tradeoff between maximizing the quality of every chunk and ensuring fairness among all video chunks for the minimum re-buffering time. The problem is constrained with the available bandwidth, the chunk deadlines, and the imposed maximum contribution constraints by users. Moreover, we propose a low-complexity algorithm to solve the proposed optimization problem. A real implementation of the system with real SVC-encoded videos and real bandwidth traces reveal the robustness and performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a non-orthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast scheme for cellular networks is proposed. This scheme combines the successive video-layer decoding in SVC with the successive interference cancellation (SIC) in NOMA, which enables a further reduction of the bottleneck effect imposed by cell-edge user equipments (UEs). Aiming at maximizing the overall video quality experienced by UEs in multiple multicast groups, the resource allocation for multiple groups and the scalable multicast scheduling within each group are formulated as a joint mixed-integer nonlinear programming problem. The formulated optimization problem is decoupled into a multi-group resource allocation (MRA) problem and multiple independent intra-group scalable multicast scheduling (IGSMS) subproblems. To solve IGSMS subproblems, we propose an optimal recursive algorithm, for which the optimal transmit power for each layer of the superposition coding needed in each iteration is derived in a closed form. The MRA problem is optimally solved via a knapsack approach. Extensive numerical results demonstrate the improved performance of the proposed NOMA-enhanced SVC multicast scheme over several baseline schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider multi-quality multicast beamforming of a video stream from a multi-antenna base station to multiple single-antenna users receiving different qualities of the same video stream, via scalable video coding (SVC). Leveraging the layered structure of SVC and exploiting superposition coding as well as successive interference cancelation, we propose a layer-based multi-quality multicast beamforming scheme. To reduce the computational complexity, we also propose a quality-based multi-quality multicast beamforming scheme, which further utilizes the layered structure of SVC and quality information of all users. Under each scheme, for given quality requirements of all users, we formulate the corresponding optimal beamforming design as a non-convex power minimization problem, and obtain a globally optimal solution for a class of special cases as well as a locally optimal solution for the general case. Then, we show that the minimum total transmission power of the layer-based power minimization problem is the same as that of the quality-based power minimization problem, although the latter incurs a lower computational complexity. Next, we consider the optimal joint layer selection and quality-based multi-quality multicast beamforming design to maximize the total utility representing the satisfaction with the received video quality for all users under a given maximum transmission power budget, which is NP-hard in general. Based on the optimal solution of the quality-based power minimization problem, we develop a greedy algorithm to obtain a near optimal solution. Finally, numerical results show that the proposed solutions achieve better performance than existing solutions. [ABSTRACT FROM AUTHOR]

Mobile broadcast/multicast video services have become highly demanded in mobile networks and require effective and low-complexity radio resource management (RRM) strategies. This paper proposes an RRM strategy based on multicast subgrouping and the scalable video coding (SVC) technique for multicast video delivery that focuses on reducing the search space of solutions and optimizes the aggregated data rate (ADR). The results in terms of ADR, spectral efficiency, and fairness among multicast users, along with the low complexity of the algorithm, show that this new scheme is adequate for real systems. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for layered media transmission in mobile broadcast systems, which is referred to as the layer-mixed forward error correction (FEC). Unlike the existing unequal error protection and layer-aware FEC which decode each layer symbols with a probability, the new approach is capable of decoding each layer data deterministically as long as enough symbols are received corresponding to the specific layer. The lower layer is always decoded prior to upper layers, which facilitates the delivery of scalable media stream, especially in mobile TV services with heterogeneous networks and terminals. In order to evaluate the performance fairly, this paper compares the minimum channel capacity required by several FEC schemes. The experimental results show that the new approach outperforms the existing schemes in severely degraded channel situations. [ABSTRACT FROM PUBLISHER]

This paper focuses on the transmission of layered source information, such as scalable video coding, over heterogeneous cellular networks. Scalable transmission enables dynamic adaption of source information to the condition of user equipment (UE) devices and, thus, is suitable for cellular networks in which the transmission link quality substantially varies over space and time. Two novel transmission schemes are proposed, namely, layered digital transmission and layered hybrid digital–analog (LHDA) transmission. Leveraging tools from stochastic geometry, a comprehensive analysis is conducted focusing on three key performance metrics: outage probability, high-definition probability, and average distortion. The results show that both proposed transmission schemes can provide a scalable video experience for UE devices. For LHDA transmission, the optimal power allocation between digital and analog transmissions is also analyzed. When the proportion of frequency resource allocated to the femtotier exceeds a certain threshold, LHDA transmission is preferable by enabling continuous quality scalability, thus avoiding the cliff effect. [ABSTRACT FROM PUBLISHER]

We propose a joint rate and power adaptation scheme to maximize the decoding quality for scalable video coding (SVC)-based video transmissions over multi-input multioutput (MIMO) systems. The rate adaptation in our proposed scheme includes selection of the best modulation and coding schemes, set of spatial channels, number of SVC layers (source coding rates), and their corresponding application layer forward error correction (APP-FEC) coding rates. The power adaptation involves the proper allocation of the power to each antenna in the MIMO system. SVC-based video transmissions require unequal error protection (UEP) for different SVC layers due to the inter-layer dependency. In most of the previous works, the bit stream of each particular SVC layer is allocated to one spatial channel and the UEP is achieved by transmitting the more important SVC layers through the spatial channels with higher channel gains. However, in our proposed scheme, the bit stream of each particular SVC layer is distributed to multiple spatial channels so that additional diversity gain can be exploited by applying APP-FEC. The UEP can also be achieved by allocating different APP-FEC coding rates on each video layer. Moreover, transmit power allocation is also effectively and jointly determined to improve the system performance. The effectiveness and favorable performance of our proposed scheme are shown by simulations with H.264 SVC traces of high-definition video clips over MIMO systems. [ABSTRACT FROM AUTHOR]

Scalable Video Coding (SVC) has been raised as a promising technique to enable flexible video transmission for mobile users with heterogeneous terminals and varying channel capacities. In this paper, we design an adaptive layer switching algorithm for on-demand scalable video service based on receiver’s buffer underflow probability (BUP). Since the low quality of channel may lead to a low buffer fullness, the buffer fullness is an indicator for reflecting the channel condition and we define BUP for characterizing the mismatch between the video bitrate and the channel throughput. Accordingly, the adaptive SVC transmission problem is formulated as the adaptive adjustment of video layers based on BUP. This allows us to optimize the attainable video quality, while keeping BUP below a desired level. To estimate BUP, we derive an analytical model based on the large deviation principles. Then, an online layer switching algorithm is proposed using this estimation model, which is capable of accommodating different channel qualities without any prior knowledge of the channel variations and of the video characteristics. We further introduce a perturbation-based layer switching approach for reducing the quality fluctuating issue caused by frequent layer switches, thus improving the viewer’s quality of experience. A system prototype is implemented to evaluate the success of the proposed method. We also conduct simulations in multiuser scenarios with real video traces and the results demonstrate that the proposed algorithm is capable of improving the playback experience, while keeping a low playback interruption rate and quality variation. [ABSTRACT FROM PUBLISHER]

The growing demand for mobile multicast services, such as Internet Protocol television (IPTV) and video streaming, requires effective radio resource management (RRM) to handle traffic with strict quality-of-service constraints over Long-Term Evolution (LTE) and beyond systems. Special care is needed to limit system performance degradation when multiple multicast streams are simultaneously transmitted. To this aim, this paper proposes an RRM policy based on a subgrouping technique for the delivery of scalable multicast video flows in a cell. Our proposal enhances the legacy multicast transmission over LTE systems by exploiting multiuser diversity and the users' channel quality feedbacks. Moreover, it is designed to take advantage of the frequency selectivity in the subgroup formation. Simulation results demonstrate the effectiveness of the proposed scheme, which outperforms existing approaches from the literature. It succeeds in achieving higher spectral efficiency and guaranteeing adequate video quality to all multicast receivers and improved quality to those with good channel conditions. [ABSTRACT FROM AUTHOR]

Providing scalable video streaming services for heterogeneous users in dynamic networked environments requires efficient and adaptive quality management mechanisms which deliver quality-customized services according to the client’s preferences and adapt the services to cope with various network conditions. In this paper, we address the issue of quality adaptation for providing personalized scalable media streaming services in dynamic network environments. We propose a differentiated adaptive quality optimization algorithm, called Scalable Video Coding Quality Adaptation algorithm (SVC-QA), which adapts streaming quality based on both system-level and client-level optimization to optimize streaming quality according to network bandwidth conditions, content characteristics, a user’s quality preferences, and buffering capacities of different client devices (e.g., mobile phones, PCs, HDTVs, etc.). Comparative studies are conducted to compare our proposed algorithms with other adaptive methods. We show that two-level SVC quality adaptation method can achieve better SVC streaming quality with both high peak signal-to-noise ratio (PSNR) and low quality variance under dynamic resource constraints. Moreover, the proposed distributed method reduces the computational complexities at the server side substantially, making it practical and flexible for providing scalable streaming services. [ABSTRACT FROM AUTHOR]

Scalable Video Coding (SVC) is an extension of H.264/Advanced Video Coding (AVC), which has good characteristics for video transmission over networks. SVC encodes a video into a base layer (BL) and multiple enhancement layers (ELs). With the degree of importance of each layer, in addition to different modulation and coding schemes (MCSs), we can assign different retry attempt limits to each layer to improve quality of experience (QoE) metrics, such as average playback bitrate and buffering ratio. For example, we can assign a slower MCS and a higher retry limit to the BL, to reduce the loss rate and maintain the playback smoothness; whereas, at the same time, we can also assign faster MCSs and lower retry limits to each of the ELs, to reduce the buffering ratio. In this paper, we present a QoE-based link adaptation (QLA) scheme for H.264/SVC video streaming over IEEE 802.11 b/g wireless LANs. We then present a multicast extension of the QLA scheme, multicast QLA (MQLA). We implemented our QLA and MQLA schemes on a Linux-based Wi-Fi protocol driver, mac80211, and built a testbed to conduct our experiments. Experiment results show that both our schemes exhibit an improved QoE performance over the default link adaptation scheme provided by the Linux wireless driver, minstrel. [ABSTRACT FROM AUTHOR]

In the multiview video plus depth (MVD) coding format, both texture and depth views are jointly compressed to represent the 3-D video content. The MVD format enables synthesis of virtual views through depth-image-based rendering; hence, distortion in the texture and depth views affects the quality of the synthesized virtual views. Bit allocation between texture and depth views has been studied with some promising results. However, to the best of our knowledge, most of the existing bit-allocation methods attempt to allocate a fixed amount of total bit rate between texture and depth views; that is, to select appropriate pair of quantization parameters for texture and depth views to maximize the synthesized view quality subject to a fixed total bit rate. In this paper we propose a scalable bit-allocation scheme, where a single ordering of texture and depth packets is derived and used to obtain optimal bit allocation between texture and depth views for any total target rates. In the proposed scheme, both texture and depth views are encoded using the quality scalable coding method; that is, medium grain scalable (MGS) coding of the Scalable Video Coding (SVC) extension of the Advanced Video Coding (H.264/AVC) standard. For varying target total bit rates, optimal bit truncation points for both texture and depth views can be obtained using the proposed scheme. Moreover, we propose to order the enhancement layer packets of the H.264/SVC MGS encoded depth view according to their contribution to the reduction of the synthesized view distortion. On one hand, this improves the depth view packet ordering when considered the rate-distortion performance of synthesized views, which is demonstrated by the experimental results. On the other hand, the information obtained in this step is used to facilitate optimal bit allocation between texture and depth views. Experimental results demonstrate the effectiveness of the proposed scalable bit-allocation scheme for texture and depth views. [ABSTRACT FROM AUTHOR]

Video and multimedia streaming services continue to grow in popularity and are rapidly becoming the largest consumers of network capacity in both fixed and mobile networks. In this article we discuss the latest advances in video compression technology and demonstrate their potential to improve service quality for consumers while reducing bandwidth consumption. Our study focuses on the adaptation of scalable, highly compressed video streams to meet the resource constraints of a wide range of portable consumer devices in mobile environments. Exploring SHVC, the scalable extension to the recently standardized High Efficiency Video Coding scheme, we show the bandwidth savings that can be achieved over current encoding schemes and highlight the challenges that lie ahead in realizing a deployable and user-centric system. [ABSTRACT FROM PUBLISHER]

Consistent video quality control is an important and practical issue for video streaming applications. Several algorithms have been developed in the literature that aims to maintain consistent quality through the entire video sequence, whereas most of them focus on non-scalable video coding. In this paper, we propose an algorithm for consistent quality control for H.264/AVC based scalable video coding (SVC), relying on a dependent distortion-quantization (D-Q) model. Such a dependent D-Q model is developed to capture the distortion behavior of frames at enhancement layers (ELs) by exploring the correlation between two successive layers. Experimental results demonstrate that the proposed model can accurately estimate the distortion of each frame at different layers in the quality, temporal, and spatial scalability. The proposed model is applied in SVC where the quantization parameter of each frame at EL is carefully selected to achieve consistent video quality given the distortion constraint. Meanwhile, model parameters are initialized using the content features extracted from the underlying video sequences, and updated using the encoded data at the frame level. Simulations show that the proposed scheme enables more stable video quality with the PSNR keeping close to the target value (i.e., small PSNR variation). [ABSTRACT FROM PUBLISHER]

Designing a real-time video-streaming system involves the challenges of, network congestion and bandwidth fluctuations, lowering the video quality. In this paper, a realtime video-streaming system is designed and implemented for scalable video coding (SVC) with an adaptive control scheme, containing macro- and micro-control, to resolve the bandwidth fluctuation and network congestion. Under macro-control, the server allocates appropriated video-streaming of SVC for heterogeneous clients based on terminal capacity and network conditions. Under micro-control, the server changes the video frame rate based on video bit rates and network bandwidth. The streaming system with the adaptive control scheme is implemented to improve the peak signal noise ratio (PSNR) by 4.01 % to 10.89 % of the Foreman and Stefan videos. [ABSTRACT FROM AUTHOR]

Ultra-high definition (UHD) which has 4 to 16 times as many pixels as existing high definition (HD) is expected as a next generation video format. To deliver UHD and HD videos simultaneously in the communications-broadcasting convergence environment, scalable video coding (SVC) is a highly attractive solution. We propose an improved scalable video coding method to achieve high coding efficiency particularly for UHD and HD videos. The basic idea is to allow large block size beyond the block size of 16x16 pixels in H.264/AVC SVC, which results in more efficient inter-layer prediction and syntax elements coding. The experimental results show that it achieves an average 5.34% reduction in BD-rate relative to H.264/AVC SVC. [ABSTRACT FROM PUBLISHER]

Temporal scalability is supported in scalable video coding (SVC) by means of hierarchical prediction structures, where the higher layers can be ignored for frame rate reduction. Nevertheless, this kind of scalability is not totally exploited by the rate control (RC) algorithms since the hypothetical reference decoder (HRD) requirement is only satisfied for the highest frame rate substream of every dependence (spatial or coarse grain scalability) layer. In this paper, we propose a novel RC approach that aims to deliver several HRD-compliant temporal resolutions within a particular dependence layer. Instead of using the common SVC encoder configuration consisting of a dependence layer per each temporal resolution, a compact configuration that does not require additional dependence layers for providing different HRD-compliant temporal resolutions is proposed. Specifically, the proposed framework for rate-controlled SVC uses a set of virtual buffers within a dependence layer so that their levels can be simultaneously controlled for overflow and underflow prevention while minimizing the reconstructed video distortion of the corresponding substreams. This in-layer multibuffer approach has been built on the top of a baseline H.264/SVC RC algorithm for variable bit rate applications. The experimental results show that our proposal achieves a good performance in terms of mean quality, quality consistency, and buffer control using a reduced number of layers. [ABSTRACT FROM AUTHOR]

In Internet Protocol TeleVision (IPTV) systems, the use of video compression results in a trade-off between random access and bandwidth consumption. Most of the time, priority is given to compression efficiency, resulting in low channel switching performance. In this paper, a Scalable Video Coding (SVC) configuration is proposed, wherein base and enhancement layer are coded in such a way that fast channel switching can be offered without impacting the access network bandwidth consumption. This is achieved by encoding a full quality slow channel switching version of the video stream in the base layer extended with a reduced quality fast switching enhancement layer. Additionally, this configuration offers backward compatibility with H.264/AVC, enabling a gradual upgrade of the IPTV system from H.264/AVC to SVC. When comparing this technique to single layer H.264/AVC, 25.0% bandwidth reduction on the access network is obtained without impacting channel switching speed, but only at the cost of a slightly reduced quality ( -1 dB PSNR) during a short transition period (maximum 48 frames). If a comparison is made with a regular SVC configuration, 39.4% bandwidth reduction on the access network during steady state is obtained. Compared to simulcast H.264/AVC, 32.0% bandwidth reduction on the core network is observed. [ABSTRACT FROM AUTHOR]

In conventional wireless systems with layered architectures, the physical (PHY) layer equally treats all data streams from the upper layers and applies the same modulation and coding schemes to them. Newer systems such as Digital Video Broadcast start to introduce hierarchical modulation schemes with SuperPosition Coding (SPC) and support data streams of different priorities. However, SPC requires specialized hardware and has high complexity, which is not desirable for handheld devices. In this paper, we propose scalable modulation (s-mod) by reusing the current mainstream modulation schemes with software-based bit remapping. The performance evaluation has shown that s-mod can achieve the same and, in some cases, even better performance than SPC with much lower complexity. We further propose how to optimize the configuration of the PHY-layer s-mod and coding schemes to maximize the utility of video streaming with scalable video coding (SVC). Simulation results demonstrate substantial performance gains using s-mod and cross-layer optimization, indicating that s-mod and SVC are a good combination for video transmission in wireless networks. [ABSTRACT FROM PUBLISHER]

We propose a new disk power management scheme for scalable video coding (SVC) video playback. Conventional disk power management techniques for video players usually prefetch video frames into buffer to allow disk to enter low-power mode, which may require significant buffer space. To address this, we exploit temporal scalability property in which multiple frame rates for the same video stream are provided, and allow selective frame prefetching with the aim of achieving specified quality levels while reducing disk energy consumption. Simulation results show that the disk energy consumption can be reduced by 8.4% on average without any noticeable quality degradation by users. [ABSTRACT FROM PUBLISHER]

This paper describes the design and implementation of a multimedia home gateway for threescreen television (3STV) service. The proposed in-home wireless network uses scalable video coding (SVC) and unequal error protection with Raptor forward error correction (FEC) for maximizing the quality of experience (QoE) over the variable-bandwidth, error-prone wireless network. The gateway incorporates (a) dynamic SVC layerswitching, which enables the server to perform selecting appropriate layers from SVC bitstreams, (b) adaptive Raptor FEC, which controls the overhead of Raptor FEC according to packet loss rate (PLR), (c) an efficient combination of (a) and (b), and (d) slice group-based selective streaming in the overall gateway architecture. The paper explains the home gateway architecture as well as experiments for performance evaluation as compared to that of traditional SVC streaming. In the experiments conducted, gains in video quality vary from 2 to 5dB in peak signal-to-noise ratio (PSNR), with corresponding subjective improvements. Overall reductions of bit rate at the input to the home gateway vary from 28% to 36%1. [ABSTRACT FROM AUTHOR]