Scalable Video Streaming Research Articles

Effective scalable video streaming transmission with TBS algorithm in an MC-CDMA system

In this paper, we propose a Scalable Video Streaming transmission technique, which used the partial channel state information over the MC-CDMA system. When we transmit the video signal in the MC-CDMA, the allocation of the SVC layer scheme is the most important to improve video quality, because the SVC signal is composed of several video layers having different priorities that can determine the video quality. To improve the quality of video, we proposed the transmission block selection (TBS) for SVC signal allocation using partial channel state information (PCSI). The proposed system supports the unequal protection (UEP) depending on video layer priorities. We evaluate the performance of the proposed scheme using simulations. The simulation results show that the proposed system provides superior performance compared to those of conventional systems.

Finite‐state Markov modelling for wireless cooperative networks

Finite-state Markov chain (FSMC) models can capture the essence of time-varying fading channels and they are important tools for wireless network protocol design and performance study. How to build FSMC models for multi-hop and multi-path wireless systems remains an open issue. In this study, the FSMC models are developed for amplify-and-forward (AF) cooperative systems with selection combining (SC) and maximum ratio combining (MRC) techniques, respectively. First, the second-order statistics, the level-crossing rate and the average fade duration, are derived based on the statistical properties of each individual path, for the AF cooperative systems with SC and MRC, respectively. The results reveal that, in addition to improving the average received signal-to-noise ratio, the diversity combining schemes also improve its second-order statistical properties. Simulation results are given to verify the accuracy of the developed FSMC models. Finally, the models are used to optimise the configuration for scalable video streaming in an AF cooperative network. Experimental results show the feasibility and advantage of applying the proposed FSMC models for assisting protocol design and optimisation in wireless cooperative networks.

Robust watermarking for resolution and quality scalable video sequence

Due to the increasing heterogeneity among the end using devices for playing multimedia content, scalable video communication attracts significant attention in recent days. As a consequence, content authentication or ownership authentication using watermarking for scalable video stream is becoming emerging research topic. In this paper, a watermarking scheme for scalable video is proposed which is robust against spatial and quality scalability. In the proposed scheme, a DC frame is generated by accumulating DC values of non-overlapping blocks for every frame in the input video sequence. DC frame sequence is up-sampled and subtracted from the original video sequence to generate residual frame sequence. Then Discrete Cosine Transform (DCT) based temporal filtering is applied on DC as well as residual frame sequence. Watermark is embedded in low pass frames of DC frames and up sampled watermark is embedded in the low pass residual frames to achieve the graceful improvement of watermark signal in successive enhancement layer. A comprehensive set of experiments are done to justify the superiority of the proposed scheme over existing literature with respect to spatial and quality adaptation attacks as well as visual quality.

Cross-Layer-Based Adaptive Video Transport Over Low Bit-Rate Multihop WSNs

A low bit-rate ZigBee-based sensor network carrying scalable video streams will be considered. A cross-layer priority algorithm that combines the state of the channel and the quality of the video traffic will be suggested to optimize the required quality of service of the video streams. The proposed algorithm prioritizes the transport of the basic frames, and thus minimizes the carried enhancement orphan frames. It also avoids transmitting the enhancement frames related to a dropped basic frame. A noticeable improvement in the end-to-end delay of the video stream was achieved, an increase in the carried base frames, and a decrease in the orphan frames provided both an enhanced quality of the received video stream and an improvement in the channel utilization.

Real-time and smooth scalable video streaming system with bitstream extractor intellectual property implementation

Network congestion causes the users cannot perform a real-time streaming service. The paper proposes a real-time and smooth scalable video coding (SVC) streaming system with a bitstream extractor intellectual property (BEIP) design. The system parses the source video to obtain the video information, moreover, adjusts adaptively streaming resolution for limited network bandwidth. The BEIP with very large scale integration (VLSI) implementation, the speed, power consumption, and chip area are 243MHz, 25mW and 1.073×1.028mm2, respectively. The IP performs high system throughput of 7.8Gbps to deal with the network traffic.

Spatial Multiple Description Coding for Scalable Video Streams

The need for adapting video stream delivery over heterogeneous and unreliable networks requires self-adaptive and error resilient coding. Network bandwidth fluctuations can be handled by means of a video coding scheme which adapts to the channel conditions. However, packet losses which are frequent in wireless networks can cause a mismatch during the reconstruction in the receiver end and result in an accumulation of errors which deteriorates the quality of the delivered video. A combination of multiple description coding in pixel domain and scalable video coding schemes which addresses both video adaptation and robustness to data loss is proposed in this paper. The proposed scheme combines error concealment with spatial video scalability. In order to improve the fidelity of the reconstructed to the original frames in presence of packet loss, a multilayer polyphase spatial decomposition algorithm is proposed. Classical multiple description methods interpolate the missing data which results in smoothing and artifact at object boundaries. The proposed algorithm addresses the quality degradation due to low-pass filtering effect of interpolation methods. We also comparatively analyze the trade-off between robustness to channel errors and coding efficiency.

Proxy-Based Multi-Stream Scalable Video Adaptation Over Wireless Networks Using Subjective Quality and Rate Models

Despite growing maturity in broadband mobile networks, wireless video streaming remains a challenging task, especially in highly dynamic environments. Rapidly changing wireless link qualities, highly variable round trip delays, and unpredictable traffic contention patterns often hamper the performance of conventional end-to-end rate adaptation techniques such as TCP-friendly rate control (TFRC). Furthermore, existing approaches tend to treat all flows leaving the network edge equally, without accounting for heterogeneity in the underlying wireless link qualities or the different rate utilities of the video streams. In this paper, we present a proxy-based solution for adapting the scalable video streams at the edge of a wireless network, which can respond quickly to highly dynamic wireless links. Our design adopts the recently standardized scalable video coding (SVC) technique for lightweight rate adaptation at the edge. Leveraging previously developed rate and quality models of scalable video with both temporal and amplitude scalability, we derive the rate-quality model that relates the maximum quality under a given rate by choosing the optimal frame rate and quantization stepsize. The proxy iteratively allocates rates of different video streams to maximize a weighted sum of video qualities associated with different streams, based on the periodically observed link throughputs and the sending buffer status. The temporal and amplitude layers included in each video are determined to optimize the quality while satisfying the rate assignment. Simulation studies show that our scheme consistently outperforms TFRC in terms of agility to track link qualities and overall subjective quality of all streams. In addition, the proposed scheme supports differential services for different streams, and competes fairly with TCP flows.

A new rateless code with unequal error protection property

In our previous work, “robust transmission of scalable video stream using modified LT codes”, an LT code with unequal packet protection property was proposed. It was seen that applying the proposed code to any importance-sorted input data, could increase the probability of early decoding of the most important parts when enough number of encoded symbols is available at the decoder’s side. In this work, the performance of the proposed method is assessed in general case for a wide range of loss rate, even when there are not enough encoded symbols at the decoder’s side. Also in this work the degree distribution of input nodes is investigated in more detail. It is illustrated that sorting input nodes in encoding graph, as what we have done in our work, has superior advantage in comparison with unequal input node selection method that is used in traditional rateless code with unequal error protection property.

A fast algorithm of bitstream extraction using distortion prediction based on simulated annealing

Scalable video streams can be extracted to meet the bandwidth limitation of different networks and end-users. Bitstream extraction is usually performed at the network proxy or gateway during transmission, where a low computational complexity is always preferred. How to quickly and accurately select the best resolution combination for a video to meet different bandwidth requirements by each user is crucial in bitstream extraction. In this paper a fast algorithm of bitstream extraction for scalable video is proposed. The interlayer dependency between the base quality layer and the first quality layer was used to predict the distortion of higher quality layers. When quality of every layer is available, the proposed method searches for the optimized combination of quality layers based on simulated annealing. Experimental results show that the proposed method provides an optimized performance, which is significantly higher than that can be achieved by the basic extraction method. Compared to the quality layer based extraction method in the reference software model of H.264/SVC (i.e., JSVM), the proposed algorithm can greatly decrease the decoding times from 2NT to only 2 without losing rate-distortion performance. Furthermore, the proposed method obtains a more smoothed video quality which is always favorable to the observer.

Distortion-Aware Scalable Video Streaming to Multinetwork Clients

<?Pub Dtl=""?> We consider the problem of scalable video streaming from a server to multinetwork clients over heterogeneous access networks, with the goal of minimizing the distortion of the received videos. This problem has numerous applications including: 1) mobile devices connecting to multiple licensed and ISM bands, and 2) cognitive multiradio devices employing spectrum bonding. In this paper, we ascertain how to optimally determine which video packets to transmit over each access network. We present models to capture the network conditions and video characteristics and develop an integer program for deterministic packet scheduling. Solving the integer program exactly is typically not computationally tractable, so we develop heuristic algorithms for deterministic packet scheduling, as well as convex optimization problems for randomized packet scheduling. We carry out a thorough study of the tradeoff between performance and computational complexity and propose a convex programming-based algorithm that yields good performance while being suitable for real-time applications. We conduct extensive trace-driven simulations to evaluate the proposed algorithms using real network conditions and scalable video streams. The simulation results show that the proposed convex programming-based algorithm: 1) outperforms the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) by about 10–15 dB higher video quality; 2) reduces average delivery delay by over 90% compared to DCCP; 3) results in higher average video quality of 4.47 and 1.92 dB than the two developed heuristics; 4) runs efficiently, up to six times faster than the best-performing heuristic; and 5) does indeed provide service differentiation among users.

On quality of experience of scalable video adaptation

In this paper, we study the quality of experience (QoE) issues in scalable video coding (SVC) for its adaptation in video communications. A QoE assessment database is developed according to SVC scalabilities. Based on the subjective evaluation results, we derive the optimal scalability adaptation track for the individual video and further summarize common scalability adaptation tracks for videos according to their spatial information (SI) and temporal information (TI). Based on the summarized adaptation tracks, we conclude some general guidelines for the effective SVC video adaptation. A rate-QoE model for SVC adaptation is derived accordingly. Experimental results show that the proposed QoE-aware scalability adaptation scheme significantly outperforms the conventional adaptation schemes in terms of QoE. Moreover, the proposed QoE model reflects the rate and QoE relationship in SVC adaptation and thus, provides a useful methodology to estimate video QoE which is important for QoE-aware scalable video streaming.

Scalable video streaming techniques over cooperative relay networks

This paper investigates a communication method using unequal loss protected layered video and explores use of this over a cooperative relay network. The method is adapted to prioritized video transmission to explore two prioritized layering (scalable) video techniques. Cooperative communication networks can reduce power consumption and benefit wireless networks, where intermediate nodes act as relays of transmitted data, increasing the coverage and network throughput. The methods are therefore evaluated in the context of a number of different relay collaboration strategies using a finite state Markov chain (FSMC) loss model for the wireless channel. Random linear codes are ideally suited to multiple path transmission because the aggregated received symbols over multiple paths assist decoding at the receiver. The results illustrate the advantages for these application scenarios using each considered strategy and analyze the impact in a relay-based network. General Terms Video communications, Relay networks, Scalable video.

Data reorganization for scalable video service with embedded mobile devices

Recent development of high-speed wireless networks and embedded systems has enabled the recording and delivery of high-performance multimedia to heterogeneous mobile users. To support heterogeneous mobile users with high-quality multimedia services, scalable video coding was introduced. In the scalable video coding (SVC), through multidimensional scalability, all types of these scalability can be exploited at the same time. However, the generated video sequences of scalable video coding are not adequate for mobile multimedia service systems since its flexibility makes non contiguous storing and retrieval of partial stream data. In this article, we propose efficient scalable video data reorganization for video servicing systems, which consist of video server and mobile clients. For video server, we reorganize scalable video streams taking into account both of decoding dependency and location in disk array storage, where disk array is widely used for storage systems of video server. In the mobile devices, we place substreams with the consideration of NAND flash memory page and block boundaries, which is storage for mobile devices. The experimental results show that the proposed reorganization of scalable video can improve the performance of mobile multimedia service systems.

Optimal 4G OFDMA Dynamic Subcarrier and Power Auction-based Allocation towards H.264 Scalable Video Transmission

In this paper, authors presented a price maximization scheme for optimal orthogonal frequency division for multiple access (OFDMA) subcarrier allocation for wireless video unicast/multicast scenarios. They formulate a pricing based video utility function for H.264 based wireless scalable video streaming, thereby achieving a trade-off between price and QoS fairness. These parametric models for scalable video rate and quality characterization are derived from the standard JSVM reference codec for the SVC extension of the H.264/AVC, and hence are directly applicable in practical wireless scenarios. With the aid of these models, they proposed auction based framework for revenue maximization of the transmitted video streams in the unicast and multicast 4G scenario. A closed form expression is derived for the optimal scalable video quantization step-size subject to the constraints of the unicast/multicast users in 4G wireless systems. This yields the optimal OFDMA subcarrier allocation for multi-user scalable video multiplexing. The proposed scheme is cognizant of the user modulation and code rate, and is hence amenable to adaptive modulation and coding (AMC) feature of 4G wireless networks. Further, they also consider a framework for optimal power allocation based on a novel revenue maximization scheme in OFDMA based wireless broadband 4G systems employing auction bidding models. This is formulated as a constrained convex optimization problem towards sum video utility maximization. We observe that as the demand for a video stream increases in broadcast/multicast scenarios, higher power is allocated to the corresponding video stream leading to a gain in the overall revenue/utility. We simulate a standard WiMAX based 4G video transmission scenario to validate the performance of the proposed optimal 4G scalable video resource allocation schemes. Simulations illustrate that the proposed optimal bandwidth and power allocation schemes result in a significant performance improvement over the suboptimal equal resource allocation schemes for scalable video transmission.

Capacity Management of Seed Servers in Peer-to-Peer Streaming Systems With Scalable Video Streams

To improve rendered video quality and serve more receivers, peer-to-peer (P2P) video-on-demand streaming systems usually deploy seed servers. These servers complement the limited upload capacity offered by peers. In this paper, we are interested in optimally managing the capacity of seed servers, especially when scalable video streams are served to peers. Scalable video streams are encoded in multiple layers to support heterogeneous receivers. We show that the problem of optimally allocating the seeding capacity to serve scalable streams to peers is NP-complete. We then propose an approximation algorithm to solve it. Using the proposed allocation algorithm, we develop an analytical model to study the performance of P2P video-on-demand streaming systems and to manage their resources. The analysis also provides an upper bound on the maximum number of peers that can be admitted to the system in flash crowd scenarios. We validate our analysis by comparing its results to those obtained from simulations. Our analytical model can be used by administrators of P2P streaming systems to estimate the performance and video quality rendered to users under various network, peer, and video characteristics.

Content-aware optimization on rate-distortion and network traffic for scalable video multicast networks

This paper aims to optimize the content-aware prioritization of scalable video multicast, which is coupled with multipath streaming and network coding based routing. It constructs multiple layer distribution meshes for the scalable video stream to minimize the total video distortion at all the receivers, determines the base layer meshes with minimum costs to maintain application-layer QoS and the layer synchronization of SVC streaming, and improves the network throughput by encouraging path-overlapping transmissions and thus allowing bandwidth sharing among different receivers for the same video layer by utilizing network coding. The targeted problem is formulated into a minimization programming in which the quality variation between layers, the transmission cost of the base layer, as well as the efficient resource utilization are jointly considered. By decomposition and dual approach, the global convex problem is solved by a two-level decentralized iterative algorithm. The implementation of the distributed algorithm is discussed with regard to the communication overhead, and the convergence performance is validated by numerical experiments. Packet-level simulations demonstrate that the proposed algorithm could approximately achieve the maximum flow rates determined by Max-Flow Min-Cut Theorem and benefit the overall received video quality.

Empirical evaluation of H.264/SVC streaming in resource-constrained multihomed mobile networks

Nomadic users of streamed multimedia content in mobile networks are often faced with resource-constrained network paths that suffer from low bandwidth. Streaming high-quality video in such a challenging scenario demands a set of highly adaptive schemes, which have not been sufficiently explored in particular for the emerging H.264 Scalable Video Coding (H.264/SVC) standard. In this paper, we empirically investigate the performance of streaming H.264/SVC scalable video streams to users in multihomed mobile networks containing multiple available transmission paths. Previous work has demonstrated the feasibility of aggregating bandwidth of multiple paths to deliver video streams when no single, sufficiently high bandwidth path is available. We focus on evaluating the enhanced performance of multipath bandwidth-aggregation streaming by exploiting a quality-layers based, H.264/SVC-specific packet prioritisation scheme for quality-aware multipath packet scheduling and selective packet dropping in case of bandwidth shortage even after aggregation. Additionally, we explore a base-layer rate control scheme for H.264/SVC delivery in ultra-low bandwidth environments. Through extensive experimentation on a realistic hardware-based testbed, we obtain a comprehensive and insightful understanding of the behaviour of H.264/SVC streams when transmitted across multiple paths in mobile networks. We quantify the improvements offered by the use of H.264/SVC-specific packet prioritisation schemes compared with an existing generic scalable video prioritisation scheme, and the benefits by the use of base-layer rate control in ultra-low bandwidth situations. The performance of the multipath streaming schemes is further compared with that of an ideal single high bandwidth path. We also identify the remaining challenges that must be overcome if such streaming schemes are to offer performance close to that of the ideal single high bandwidth path.

Integer-multiple-spacing-based scheduling for multimedia applications in IEEE 802.11e HCCA wireless networks

This paper is concerned with improving bandwidth utilization while guaranteeing quality-of-service (QoS) requirements for multimedia applications in IEEE 802.11e HCCA wireless networks. We propose two integer-multiple-spacing-based (IMS-based) designs: the IMS-based-δ and IMS-based-l designs. In the IMS-based designs, the scheduling spacing of any traffic must be an integer multiple of the minimum spacing. The IMS-based designs have more potential to improve the bandwidth utilization because they schedule traffic with longer spacings compared with the prior designs. Besides the improvement of the bandwidth utilization, the IMS-based-δ design can guarantee the packet delay requirements, where a δ factor is introduced to ensure that the bandwidth utilization must benefit from longer spacings, while the IMS-based-l design can guarantee the packet loss requirements. Numerical results show that the improvement of the bandwidth utilization for the IMS-based-δ and -l designs can be up to 7.7% and 56% or more, respectively, compared with the prior designs.To illustrate the utility of our designs, we also develop two schemes applying the IMS-based-δ design to the scalable video streaming transmission over 802.11e HCCA wireless networks. Numerical results show that our schemes can transmit scalable video streamings efficiently, particularly when the physical layer transmission rate (PHY rate) is large.

Cross Layer Adaptation with QoS Guarantees for Wireless Scalable Video Streaming

In this paper, a cross-layer adaptation scheme is proposed for quality of service (QoS) provision in the scalable video streaming of high definition (HD) content. The cross-layer parameters, which contain the video rate, payload length of a packet, the mode of modulation and coding scheme (MCS), can be dynamically adapted to minimize distortion of a video streaming under the given delay bound. Based on the channel quality and rate-distortion parameters, the proposed scheme formulates the problem of parameter selection into an optimization problem. Simulation results show that our approach guarantees video quality under QoS constraints.

Congestion-aware quality-adaptive streaming of scalable video

Internet video streaming is a hot topic in multimedia systems. A large variety of devices (computers, mobile phones, TVs, etc.) are connected to the Internet via wired or wireless networks and are capable of receiving and decoding HD video content. To enable new services like HD video streaming (e.g., online video rental), the Internet’s infrastructure was enhanced. But the Internet is still a best-effort network, which does not implement quality-of-service or admission control, resulting in time-varying bandwidth and packet delay, packet loss and network congestion. Because video streaming accounts for a considerable amount of the Internet’s traffic, video streaming needs additionally to be congestion-aware, to avoid a congestion collapse of the Internet. The Transmission Control Protocol (TCP) can adapt to changing network conditions and is currently the de facto standard protocol for congestion-aware and reliable data transmission in the Internet. This fact gave TCP-based video streaming a huge momentum. Consequently, this thesis investigates TCP-based adaptive video streaming for the Internet. The main goal is to provide a solution for congestion-aware video streaming, while still being able to achieve a reasonable performance in error-prone networks. To complement existing work on congestion-aware adaptive streaming, this thesis makes six contributions. (1) The baseline performance of TCP-based adaptive streaming is identified by means of an evaluation of different adaptive streaming approaches. The results represent a reference for further investigations. (2) An investigation on the influence of TCP’s behavior in presence of packet loss on the video streaming performance. (3) To overcome the shortcomings of TCP-based video streaming (single TCP connections fail to deliver a good performance in case of packet loss), a new approach to video streaming based on multiple request-response streams was introduced. The novelty of this system is that it is able to make use of multiple HTTP-based request-response streams while still providing TCP-friendliness. (4) A performance model of the HTTP-based request-response streams was developed, to estimate the influence of the system parameters and the network characteristics on the throughput performance. (5) A comprehensive evaluation of the HTTP-based request-response streams under diverse network conditions was conducted, to validate the model’s estimations. Additionally, the TCP-friendliness was evaluated, showing that request-response streaming systems can be configured to achieve TCP-friendliness. (6) A cellular network with high bandwidth fluctuations and RTTs was used to investigate the performance of the request-response streaming system in a mobile video streaming scenario. The results indicate that the streaming system can make good use of the available bandwidth, while the number of quality switches is kept low. While aggregating multiple TCP connections to improve the TCP streaming performance is quite common, usually the improvement comes at the cost of high deployment effort. By placing the streaming logic at the client, request-response streams can avoid this complexity. Additionally, this client-driven approach responds faster to changing network conditions and enables easy recovery from connection stalls or aborts, because the control loop is at the client. To improve the network efficiency and the scalability in terms of number of clients served, HTTP-based request-response streams can utilize HTTP proxies and caches.