Layered Video Streaming Research Articles

Using packet trimming at the edge for in-network video quality adaption

This paper describes the effects of running in-network quality adaption by trimming the packets of layered video streams at the edge. The video stream is transmitted using the BPP transport protocol, which is like UDP, but has been designed to be both amenable to trimming and to provide low-latency and high reliability. The traffic adaption uses the Packet Wash process of Big Packet Protocol (BPP) on the transmitted Scalable Video Coding (SVC) video streams as they pass through a network function which is BPP-aware and embedded at the edge. Our previous work has either demonstrated the use of Software Defined Networking (SDN) controllers to implement Packet Wash directly, or the use of a network function in the core of the network to do the same task. This paper presents our effort to deploy and evaluate such a process at the edge, highlighting the packet trimming algorithm and showing the packet trimming effects on the streams. We compare the performance of transmitting video using BPP and the Packet Wash trimming, against alternative transmission schemes, namely UDP and HTTP adaptive streaming (HAS), presenting a number of quality parameters. The results demonstrate that providing traffic engineering using in-network quality adaption using packet trimming, provides high quality at the receiver.

Residual packet loss rate analysis of 2-D parity forward error correction

To improve the robustness of video communications over IP networks against packet losses, numerous IPTV and broadcasting standards have adopted the 2D application-layer forward error correction (FEC) method presented in Pro-MPEG COP3. This method uses a two-dimensional encoding matrix in which redundant checksums for each row and each column of the data matrix are generated and transmitted with the data packets. The approach has been recently extended and applied to layered video streaming. But despite its wide adoption and importance, a formal analysis of the correction performance of the Pro-MPEG COP3’s 2D FEC method is still lacking. In this paper, we formulate and solve the problem using an abstract mathematical framework, which can be used also for some natural extensions of this method. We derive tight bounds on the residual packet loss rate as a function of the 2D FEC matrix dimensions, and the packet loss rate assuming that the losses are independently and randomly distributed. We then provide simple approximations on these bounds for low packet loss rates. The analysis leads to the observation that the addition of a single checksum packet to the Pro-MPEG COP3 method would lead to a significant reduction in residual packet loss rate. The expressions derived are validated experimentally using Monte Carlo simulations. We also apply the results to the case of packet losses occurring in bursts. Finally, we study the impact of the matrix dimensions on the performance of the 2D FEC method, leading to valuable recommendations to system designers.

Near-Instantaneously Adaptive Multi-Set Space-Time Shift Keying for UAV-Aided Video Surveillance

Unmanned Aerial Vehicles (UAV) are more suitable for surveillance systems than their traditional stationary counterparts. To meet the associated demanding video compression requirements, the H.265/High Efficiency Video Coding (HEVC) codec is invoked. Its scalable video coding extension is capable of supporting diverse video resolutions by encoding the video clips captured into multiple layers, namely the Base Layer (BL) and several Enhancement Layers (EL). In this treatise, we propose a multi-functional Multiple-Input Multiple-Output (MIMO) transceiver relying on Multi-Set Space-Time Shift Keying (MS-STSK) for UAV-aided near-instantaneously adaptive layered video streaming, which is capable of promptly varying the throughput as a function of both the estimated channel quality as well as of the UAV mobility, while maintaining near-flawless video quality. Additionally, we invoke EXtrinsic Information Transfer (EXIT) charts for characterizing our Unequal Error Protection (UEP) based video transceiver with the aid of near-capacity channel coding. Some of the perceptually less important ELs may have to be dropped during instances of low channel quality to retain the robustness of the transmitted video stream when a low-throughput MIMO configuration is activated. The simulation results show that our proposed UEP assisted adaptive system is capable of attaining the best Y-Peak SNR (PSNR) performance in comparison to both its non-adaptive and Equal Error Protection (EEP) counterparts.

Distributed Caching Algorithms in the Realm of Layered Video Streaming

Distributed caching architectures have been proposed for bringing content close to requesters, and the key problem is to design caching algorithms for reducing content delivery delay, which determines to an extent the user Quality of Experience (QoE). This problem obtains an interesting new twist with the advent of advanced layered-video encoding techniques such as Scalable Video Coding. In this paper, we show that the problem of finding the caching configuration of video encoding layers that minimizes delivery delay for a network operator is NP-Hard, and we establish a pseudopolynomial-time optimal solution by using a connection with the multiple-choice knapsack problem. Next, we design caching algorithms for multiple network operators that cooperate by pooling together their co-located caches, in an effort to aid each other, so as to avoid large delays due to fetching content from distant servers. We derive an approximate solution to this cooperative caching problem by using a technique that partitions the cache capacity into amounts dedicated to own and other operators’ caching needs. Trace-driven evaluations demonstrate up to 25 percent reduction in delay over existing caching schemes. As a side benefit, our algorithms achieve smoother playback for video streaming applications, with fewer playback stalls and higher decoded quality.

Random Linear Network Coding for Wireless Layered Video Broadcast: General Design Methods for Adaptive Feedback-Free Transmission

This paper studies the problem of broadcasting layered video streams over heterogeneous single-hop wireless networks using feedback-free random linear network coding (RLNC). We combine RLNC with unequal error protection (UEP) and our main purpose is twofold: to systematically investigate the benefits of UEP+ RLNC layered approach in servicing users with different reception capabilities and to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To these ends, we study “expected percentage of decoded frames” as a key content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key system, video, and channel parameters. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users’ performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is very small and the adaptive selection of number of video layers further closes the gap.

Layer rate allocation optimization algorithm with user cluster}{Layer rate allocation optimization algorithm with user cluster

The layer rate optimization of a video layered multicast, in heterogeneous network, includes the number of layers, layer rate, and bandwidth of the user links. In order to solve the NP-hard problem in layer rate optimization, a Layer Rate Allocation Optimization with User Cluster (UC-LRAO) algorithm is proposed. The number of users in each layer and the corresponding user bandwidth carrying video streaming is obtained according to the total user number. Then the video streaming link bandwidth of users of each layer is allocated by introducing the Edmonds-Karp Max-flow Min-cut algorithm and intra-layer network coding. Finally, according to the expected layer number of the layered video streaming, the video streaming is layered again and reconstructed by clustering the users. Then, the layer rate and link bandwidth are optimized and allocated. Simulation results show that the proposed algorithm can improve the system throughput.

Optimizing broadcast duration for layered video streams in cellular networks

We study the layered video transmission optimization problem in the cellular networks, in which all User Equipments (UEs) require the same video content simultaneously via the cellular downlink transmission from the Base Station (BS) and Device-to-Device (D2D) transmission from other UEs. First, we propose a probability-based framework for each video layer to measure the video playback quality in terms of the outage probability. Next, the layered video transmission optimization problem is formulated as a Peak Signal-to-Noise Ratio (PSNR) loss minimization problem, which is then converted to an unmatured probability minimization problem by adding a differentiation weight on each layer based on its importance to the playback quality. In addition, we prove the formulated problem to be a log-convex optimization problem. Finally, we conduct extensive simulations to show that the proposed approach achieves the optimal allocation of the broadcast duration for each layer under various network conditions.

Adaptive-Truncated-HARQ-Aided Layered Video Streaming Relying on Interlayer FEC Coding

Interlayer forward error correction (IL-FEC) coding constitutes an effective unequal error protection (UEP) scheme conceived for transmitting layered video over wireless channels. In contrast to traditional UEP schemes, it operates by embedding extra information concerning the base layer (BL) into the enhancement layers (ELs) without requiring extra transmission resources. The received EL packets assist in the decoding of the BL to reduce the distortion of the reconstructed video. The optimum scheduling of the IL-FEC coded layered video streaming in a truncated hybrid automatic repeat request (THARQ)-aided system is an open problem. Hence, in this paper, we conceive an adaptive THARQ (ATHARQ) algorithm for finding the most appropriate scheduling of the IL-FEC coded layered video packets for the sake of minimizing the video distortion under the constraint of a given total number of transmission time slots (TSs). Furthermore, we develop a method of online coding-rate optimization algorithm for our IL-ATHARQ transmission scheme to find the best FEC code rate distribution among the video layers that results in the lowest possible video distortion. When using a recursive systematic convolutional (RSC) code, our simulation results show that the proposed rate-optimized (RO) IL-ATHARQ system outperforms the traditional THARQ transmission scheme by about 5.3 dB of $E_{b}/N_{0}$ at a peak signal-to-noise ratio (PSNR) of 38.5 dB. Viewing the improvements in terms of the video quality, 2.5 dB of PSNR improvement is attained at an $E_{b}/N_{0}$ of 15 dB.

Resource Allocation Strategies for Network-Coded Video Broadcasting Services Over LTE-Advanced

Video service delivery over 3GPP Long Term Evolution-Advanced (LTE-A) networks is gaining momentum with the adoption of the evolved Multimedia Broadcast Multicast Service (eMBMS). In this paper, we address the challenge of optimizing the radio resource allocation process so that heterogeneous groups of users, according to their propagation conditions, can receive layered video streams at predefined and progressively decreasing service levels matched to respective user groups. A key aspect of the proposed system model is that video streams are delivered as eMBMS flows that utilize the random linear network coding (NC) principle. Furthermore, the transmission rate and NC scheme of each eMBMS flow are jointly optimized. The simulation results show that the proposed strategy can exploit user heterogeneity to optimize the allocated radio resources while achieving desired service levels for different user groups.

A Tutorial and Review on Inter-Layer FEC Coded Layered Video Streaming

Layered video coding creates multiple layers of unequal importance, which enables us to progressively refine the reconstructed video quality. When the base layer (BL) is corrupted or lost during transmission, the enhancement layers (ELs) must be dropped, regardless whether they are perfectly decoded or not, which implies that the transmission power assigned to the ELs is wasted. For the sake of combating this problem, the class of inter-layer forward error correction (IL-FEC) solutions, also referred to as layer-aware FEC (LA-FEC), has been proposed for layered video transmissions, which jointly encode the BL and the ELs, thereby protecting the BL using the ELs. This tutorial aims for inspiring further research on IL-FEC/LA-FEC techniques, with special emphasis on the family of soft-decoded bit-level IL-FEC schemes.

Efficient content delivery scheme for layered video streaming in large-scale networks

Providing efficient layered video streaming to heterogeneous users in varying network conditions requires dynamic bandwidth allocation, efficient data scheduling and incentives. In layered streaming, the video stream is composed of hierarchically encoded sub-stream layers namely the base layer and enhancements layers. We consider a scenario where receiver peers use a pull-based approach to adjust the video quality level to their terminal and network capacities by subscribing to a different number of layers. In this context, in order to take advantage of the available bandwidth in the network and to enhance end users Quality-of-Experience (QoE), we propose a novel approach that efficiently allocates sender peers׳ upload bandwidth to receiver peers. The upstream peer bandwidth is allocated depending on the quality level (requested layers) of the receiver peers, starting by allocating bandwidth for the lower layers first. In order to allocate bandwidth for a certain layer, an auction game is established to distribute the bandwidth among the receiver peers, where the sender peers “sell” their items (upload bandwidth) according to bids submitted by receiver peers. The main goal of this approach is to favor high priority peers while ensuring a minimum quality level to all peers. The proposed bandwidth allocation mechanism is paired with efficient scheduling mechanism for layered streaming. It aims to fully take advantage of the allocated bandwidth while respecting the layers dependency of the stream and the data blocks playback deadline. Extensive evaluations are conducted to compare our proposed algorithm with other bandwidth allocation strategies for layered video streaming. The obtained results show the effectiveness of our model in terms of video quality, useless chunks ratio and bandwidth utilization under different network/streaming conditions.

Avoiding Quality Bottlenecks in P2P Adaptive Streaming

This paper addresses the problem of quality bottleneck in adaptive SVC streaming. Quality bottleneck occurs in adaptive streaming systems when the desired video quality cannot be obtained even if the network capabilities are sufficient. In the context of SVC layered video streaming, we have observed that enhancement layers remain around the video source and fail to reach all the participating peers. To overcome this problem, we propose an adaptive SVC streaming solution that cooperatively integrates strategies of overlay formation, data scheduling and content adaptation. Performance evaluation using simulations shows that the proposed streaming solution reduces the quality bottleneck, increases churn-tolerance and optimizes bandwidth utilization.

Layered P2P video streaming using asymmetric P2P topology and membership management

Peer-to-peer (P2P) video streaming applications are widely popular, e.g. PPstream and PPlive, because of higher transmission speed and data availability. A fact of P2P streaming is that different peers have different (asymmetric) capabilities for resource sharing, and thus, some asymmetric P2P (A-P2P) topology and membership management schemes should be adopted among P2P nodes having heterogeneous computing and communicating capabilities. Our research focuses on designing a novel A-P2P streaming architecture with a dedicated codec scheme that applies multiple description features into the scalable extension of H.264/AVC, which is adaptive and error-robust enough to tackle challenges in the A-P2P network environment. In the streaming architecture, our proposed device-aware P2P topology management is responsible for constructing a hierarchical membership-tree based on the capacity of upstream bandwidth and round-trip time. In addition, the buffer-aware scheduling scheme is able to determine whether the peer needs to reconnect to a proper source provider or not, based on the buffer status. In our experiments, corresponding performances, e.g. average peer-join time and average peak signal-to-noise ratio, were measured and demonstrated.

Piece selection algorithms for layered video streaming in P2P networks

This paper introduces the piece selection problem that arises when streaming layered video content over peer-to-peer networks. The piece selection algorithm decides periodically which pieces to request from other peers (network nodes) for download. The main goal of the piece selection algorithm is to provide the best possible quality for the available bandwidth. Our recommended solution approaches are related to the knapsack problem. In this paper, a number of layered piece picking algorithms are presented and they are compared to each other. In a competitive analysis, the presented online algorithms are compared to an optimal offline algorithm.

SVDN: packetization and layer synchronization for scalable video delivery over peer-to-peer networks

Layered video streaming can achieve dynamic video quality adaptation according to end user device capabilities, network conditions, and user preferences. In layered video streaming, synchronization between different video layers and packetization are two essential design challenges to facilitate video quality adaptation. This paper proposes SVDN--a novel Real-Time Scalable Video Delivery system using Peer-to-Peer (P2P) Networks--and focuses on the following perspectives: (1) a distributed video layer synchronization algorithm for P2P networks is proposed, which is the key algorithm facilitating dynamic video quality adaptations for live video streaming; (2) the corresponding packetization design for fixed chunk size is presented, which can fully utilize chunk space. Both Variable Bit Rate and Constant Bit Rate are supported by the packetization method; (3) an adaptive chunk size determination algorithm is proposed to estimate a fixed chunk size for each video layer, which further improves the packetization performance. Evaluation of the implementation shows that SVDN significantly improves the bandwidth usage when compared with existing packetization solutions for fixed chunk sizes. The average minimum packetization overhead of the state of the art solution ranges from 8.5 to 15 %, while SVDN can achieve virtually zero padding overhead and at the same time fully support spatial, temporal and quality layer switching of H.264/Scalable Video Coding encoded video.

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.

Churn-aware optimal layer scheduling scheme for scalable video distribution in super-peer overlay networks

To model a layered video streaming system in super-peer overlay networks that faces with heterogeneity and volatility of peers, we formulate a layer scheduling problem from understanding some constraints such as layer dependency, transmission rule, and bandwidth heterogeneity. To solve this problem, we propose a new layer scheduling algorithm using a real-coded messy genetic algorithm, providing a feasible solution with low complexity in decision. We also propose a peer-utility-based promotion algorithm that selects the most qualified neighbor to guarantee the sustained quality of streaming despite high intensity of churn. Simulation results show that the proposed layer scheduling scheme can achieve the most near-optimal solutions compared to the four conventional scheduling heuristics in the average streaming ratio. It also highly outperforms those with different peer selection strategies in terms of the average bandwidth (6.9 % higher at least) and the variation of utilization (11.3 % lower at least).

An efficient playout smoothing mechanism for layered streaming in P2P networks

Layered video streaming in peer-to-peer (P2P) networks has drawn great interest, since it can not only accommodate large numbers of users, but also handle peer heterogeneity. However, there’s still a lack of comprehensive studies on chunk scheduling for the smooth playout of layered streams in P2P networks. In these situations, a playout smoothing mechanism can be used to ensure the uniform delivery of the layered stream. This can be achieved by reducing the quality changes that the stream undergoes when adapting to changing network conditions. This paper complements previous efforts in throughput maximization and delay minimization for P2P streaming by considering the consequences of playout smoothing on the scheduling mechanisms for stream layer acquisition. The two main problems to be considered when designing a playout smoothing mechanism for P2P streaming are the fluctuation in available bandwidth between peers and the unreliability of user-contributed resources—particularly peer churn. Since the consideration of these two factors in the selection and scheduling of stream layers is crucial to maintain smooth stream playout, the main objective of our smoothing mechanism becomes the determination of how many layers to request from which peers, and in which order. In this work, we propose a playout smoothing mechanism for layered P2P streaming. The proposed mechanism relies on a novel scheduling algorithm that enables each peer to select appropriate stream layers, along with appropriate peers to provide them. In addition to playout smoothing, the presented mechanism also makes efficient use of network resources and provides high system throughput. An evaluation of the performance of the mechanism demonstrates that the proposed mechanism provides a significant improvement in the received video quality in terms of lowering the number of layer changes and useless chunks while improving bandwidth utilization.

Layered Video Transmission with Network Coding in a Cooperative Virtual MIMO Cellular Relay Networks

In this letter, we propose a layered video streaming technique that combines network coding (NC), multiple-input multiple-output (MIMO), and hierarchical modulation (HM) over cellular relay networks. We provide a performance analysis of different transmission modes of NC and MIMO in terms of the error rate in video layers, which is reflected in the total layered-video quality. The HM is used to differentiate the error rates among video layers. The simulation results show that the NC, the MIMO spatial multiplexing (SM), and the combination of both the NC and MIMO-SM gives video-quality gains of about 1.9dB, 6dB, and 12dB maximally, respectively, compared to the conventional single-input and single-output (SISO) single relay network (SRN) system.

Unequal error protection under bitrate constraint for video streaming over internet

This article describes a simple packet-level FEC system suitable for unequal error protection of layered video streams, that we called TAPIOCA (in French, Transport Audiovisuel avec Protection Inegale des Objets et Controle d'Admission). It is designed in a way that the FEC overhead induced by redundant packets is perfectly controlled by the sender. In order to achieve that, TAPIOCA calculates on-the-fly the optimal erasure code to be used, video data unit by video data unit, under a given bitrate constraint. In addition, and contrary to the well-known PET (Priority Encoding Transmission) system, the video data units of each layer are encoded separately. This is especially useful when all layers are not output from the video coder at the same time. Simulation results for MPEG-4 video streaming show that the proposed FEC system can be very efficient even if packet losses are due to network congestion. Moreover, comparison with PET system shows that TAPIOCA exhibits better performance, considering criteria including the decodable frame rate, protection system efficiency and computational cost.