In this study, we propose a mechanism called adaptive failsoft control to address peak traffic in mobile live streaming, using a chasing playback function. Although a cache system is avaliable to support the chasing playback function for live streaming in a base station and device-to-device communication, the request concentration by highlight scenes influences the traffic load owing to data unavailability. To avoid data unavailability, we adapted two live streaming features: (1) streaming data while switching the video quality, and (2) time variability of the number of requests. The second feature enables a fallback mechanism for the cache system by prioritizing cache eviction and terminating the transfer of cache-missed requests. This paper discusses the simulation results of the proposed mechanism, which adopts a request model appropriate for (a) avoiding peak traffic and (b) maintaining continuity of service.

Mobile video traffic is expected to increase explosively because of the proliferating number of Wi-Fi terminals. An overloaded multiple-input multiple-output (MIMO) technique allows the receiver to implement smaller number of antennas than the transmitter in exchange for degradation in video quality and a large amount of computational complexity for postcoding at the receiver side. This paper proposes a novel linear precoder for high-quality video streaming in overloaded multiuser MIMO systems, which protects visually significant portions of a video stream. A low complexity postcoder is also proposed, which detects some of data symbols by linear detection and the others by a prevoting vector cancellation (PVC) approach. It is shown from simulation results that the combination use of the proposed precoder and postcoder achieves higher-quality video streaming to multiple users in a wider range of signal-to-noise ratio (SNR) than a conventional unequal error protection scheme. The proposed precoder attains 40dB in peak signal-to-noise ratio even in poor channel conditions such as the SNR of 12dB. In addition, due to the stepwise acquisition of data symbols by means of linear detection and PVC, the proposed postcoder reduces the number of complex additions by 76% and that of multiplications by 64% compared to the conventional PVC.

In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.

Wireless video sensor networks address problems, such as low power consumption of sensor nodes, low computing capacity of nodes, and unstable channel bandwidth. To transmit video of distributed video coding in wireless video sensor networks, we propose an efficient scalable distributed video coding scheme. In this scheme, the scalable Wyner-Ziv frame is based on transmission of different wavelet information, while the Key frame is based on transmission of different residual information. A successive refinement of side information for the Wyner-Ziv and Key frames are proposed in this scheme. Test results show that both the Wyner-Ziv and Key frames have four layers in quality and bit-rate scalable, but no increase in complexity of the encoder.

This paper deals with a broadcast network with a server and many users. The server has files of content such as music and videos, and each user requests one of these files, where each file consists of some separated layers like a file encoded by a scalable video coding. On the other hand, each user has a local memory, and a part of information of the files is cached (i.e., stored) in these memories in advance of users' requests. By using the cached information as side information, the server encodes files based on users' requests. Then, it sends a codeword through an error-free shared link for which all users can receive a common codeword from the server without error. We assume that the server transmits some layers up to a certain level of requested files at each different transmission rate (i.e., the codeword length per file size) corresponding to each level. In this paper, we focus on the region of tuples of these rates such that layers up to any level of requested files are recovered at users with an arbitrarily small error probability. Then, we give inner and outer bounds on this region.

High-resolution image and video communication in home networks is highly expected to proliferate with the spread of Wi-Fi devices and the introduction of multiple-input multiple-output (MIMO) systems. This paper proposes a joint transmission and coding scheme for broadcasting high-resolution video streams over multiuser MIMO systems with an eigenbeam-space division multiplexing (E-SDM) technique. Scalable video coding makes it possible to produce the code stream comprised of multiple layers having unequal contribution to image quality. The proposed scheme jointly assigns the data of scalable code streams to subcarriers and spatial streams based on their signal-to-noise ratio (SNR) values in order to transmit visually important data with high reliability. Simulation results show that the proposed scheme surpasses the conventional unequal power allocation (UPA) approach in terms of both peak signal-to-noise ratio (PSNR) of received images and correct decoding probability. PSNR performance of the proposed scheme exceeds 35dB with the probability of over 95% when received SNR is higher than 6dB. The improvement in average PSNR by the proposed scheme compared to the conventional UPA comes up to approx. 20dB at received SNR of 6dB. Furthermore, correct decoding probability reaches 95% when received SNR is greater than 4dB.

In this work, we study efficient scheduling with network coding in a scalable video coding (SVC) multicast system. Transmission consists of two stages. The original SVC packets are multicasted by the server in the first stage and the lost packets are retransmitted in the second stage. With deadline constraint, the consumer can be only satisfied when the requested packets are received before expiration. Further, the hierarchical encoding architecture of SVC introduces extra decoding delay which poses a challenge for providing acceptable reconstructed video quality. To solve these problems, instantly decodable network coding is applied for reducing the decoding delay, and a novel packet weighted policy is designed to better describe the contribution a packet can make in upgrading the recovered video quality. Finally, an online packet scheduling algorithm based on the maximal weighted clique is proposed to improve the delay, deadline miss ratio and users' experience. Multiple characteristics of SVC packets, such as the packet utility, the slack time and the number of undelivered/wanted packets, are jointly considered. Simulation results prove that the proposed algorithm requires fewer retransmissions and achieves lower deadline miss ratio. Moreover, the algorithm enjoys fine recovery video quality and provides high user satisfaction.

How to manage the video streaming in future networks is becoming a more and more challenging issue. Recent studies on vehicular networks depict a new picture of the next generation Intelligent Transport System (ITS), with high level road safety and more comfortable driving experience. To cope with the heterogeneous network development for the next generation cellular network, centralized medium control is promising to be employed upon Road Side Unit (RSU). To accommodate the QoS constraints posed by video services in vehicular networks, the scalable video coding (SVC) scheme in H.264/AVC standard family offers spatial and temporal scalabilities in the video dissemination. In this paper, we target the resource allocation and layer selection problem for the multi-user video streaming over highway scenario, by employing SVC coding scheme for the video contents. We propose a Resource Allocation and Layer Selection (RALS) algorithm, which explicitly takes account of the utility value of each Group Of Picture (GOP) among all the vehicular users. Simulation results show that our proposed RALS algorithm outperforms the comparison schemes in typical scenarios.

We seek a resource allocation algorithm through carrier allocation and modulation mode selection for improving the quality of service (QoS) that can adapt to various screen sizes and dynamic channel variations. In terms of visual quality, the expected visual entropy (EVE) is defined to quantify the visual information of being contained in each layer of the scalable video coding (SVC). Fairness optimization is conducted to maximize the EVE using an objective function for given constraints of radio resources. To conduct the fairness optimization, we propose a novel approximation algorithm for resource allocation for the maximal EVE. Simulations confirm that the QoS in terms of the EVE or peak signal to noise ratio (PSNR) is significantly improved by using the novel algorithm.

In this paper, we propose a novel layered scalable- multiple description coding (LS-MDC) which offers the benefits of both scalable video coding and multiple description coding for robust video transmission over packet lossy networks. In the proposed LS-MDC method, multiple descriptions including base layer, enhancement layers, and their corresponding FEC parity data are allocated into two network paths of a path diversity system. Unlike the conventional approaches, the source base/enhancement data and their own parities in the proposed method are not transmitted together but are transferred over different paths. Therefore, the effect of burst packet losses can be effectively reduced for the descriptions. Furthermore, in order to minimize the overall distortion for the LS-MDC system and exploit the benefits of path diversity, we also propose an optimal rate allocation scheme that can adaptively control the transmission rate as well as the channel coding rate for media senders. Experiments show that the proposed method provides much better peak signal-to-noise ratio (PSNR) than conventional MDC techniques.

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

This paper proposes Burst Error Resilient coding (BRC) technology in mobile broadcasting network. The proposed method utilizes Scalable Video Coding (SVC) and Forward Error Correction (FEC) to overcome service outage due to burst loss in mobile network. The performance evaluation is performed by comparing PSNR of SVC and the proposed method under MBSFN simulation channel. The simulation result shows PSNR of SVC equal error protection (EEP), unequal error protection (UEP) and proposed BRC using Raptor FEC code.

Scalable video coding with different modulation and coding schemes (MCSs) applied to different video layers is very appropriate for wireless multicast services because it can provide different video quality to different users according to their channel conditions, and a promising solution to handle packet losses induced by fading wireless channels is the use of layered hybrid FEC/ARQ scheme according to light-weight feedback messages from users about how many packets they have received. It is important to choose an appropriate MCS for each layer, decide how many parity packets in one layer should be transmitted, and determine the resources allocated to multiple video sessions to apply scalable video coding to wireless multicast streaming. We prove that such resource allocation problem is NP-hard and propose an approximate optimal algorithm with a polynomial run time. The algorithm can get the optimal transmission configuration to maximize the expected utility for all users where the utility can be a generic non-negative, non-decreasing function of the received rate. The results from simulations revealed that our algorithm offer significant improvements to video quality over a nave algorithm, an optimal algorithm without feedback from users, and an algorithm with feedback from designated users, especially in scenarios with multiple video sessions and limited radio resources.

In this letter, we propose a framework for scalable video multicast, which exploits the scalability of scalable video and the multiuser diversity of OFDMA systems. We further propose a resource allocation algorithm which guarantees the base-quality video for all users, and improves the transmission efficiency for users with good channel conditions.

Scalable video coding offers efficient video transmission to a variety of display devices over heterogeneous and error-prone networks. Scalable video coding has been strenuously researched in recent years and state-of-the-art international coding with scalability has been standardized as SVC, which is an extension of H.264/AVC. This paper summarizes the recent advanced research that has been done for improving the quality and reducing the complexity of scalable video coding (including SVC), as well as for improving the quality assessment techniques. It is intended to give researchers a critical, technical overview of what is required to develop more efficient scalable video coding in the future.

We propose a distributed node selection (DNS) scheme that guarantees quality of service (QoS) of the scalable video broadcasting system over wireless channels. The proposed DNS scheme chooses the destination node based on the SVC layer information, and it selects the best relay from a set of competing candidate nodes by considering two factors: 1) wireless channel conditions between destination and relay candidates and 2) scalable video's layer information. In simulations, the performance of the proposed scheme in terms of quality gains, complexity (overhead) and applicability was examined.

For the panoramic video streaming service, this letter proposes a visual perception-based view navigation trick mode (VP-VNTM) that reduces bandwidth requirements by adjusting the quality of transmitting views in accordance with the view navigation velocity without decreasing the user's visual sensitivity. Experiments show that the proposed VP-VNTM reduces bandwidth requirements by more than 44%.

Scalable video coding (SVC) was standardized as an extension of H.264/AVC by the JVT (Joint Video Team) in Nov. 2007. The biggest feature of SVC is multi-layered coding where two or more video sequences are compressed into a single bit-stream. This letter proposes a fast block mode decision algorithm in spatial enhancement layer of SVC. The proposed algorithm achieves early decision by limiting the number of candidate modes for block with certain characteristic called same motion vector block (SMVB). Our proposed method reduces the complexity, in terms of encoding time by up to 66.17%. Nevertheless, it shows negligible PSNR degradation by only up to 0.16 dB and increases the bit-rate by only up to 0.64%, respectively.

This paper proposes a new selective encryption scheme and a key management scheme for layered access control of H.264/SVC. This scheme encrypts three domains in hierarchical layers using different keys: intra prediction modes, motion vector difference values and sign bits of texture data. The proposed scheme offers low computational complexity, low bit-overhead, and format compliance by utilizing the H.264/SVC structure. It provides a high encryption efficiency by encrypting domains selectively, according to each layer type in the enhancement-layer. It also provides confidentiality and implicit authentication using keys derived in the proposed key management scheme for encryption. Simulation results show the effectiveness of the proposed scheme.

In this paper, we introduce layered low-density generator matrix (Layered-LDGM) codes for super high definition (SHD) scalable video systems. The layered-LDGM codes maintain the correspondence relationship of each layer from the encoder side to the decoder side. This resulting structure supports partial decoding. Furthermore, the proposed layered-LDGM codes create highly efficient forward error correcting (FEC) data by considering the relationship between each scalable component. Therefore, the proposed layered-LDGM codes raise the probability of restoring the important components. Simulations show that the proposed layered-LDGM codes offer better error resiliency than the existing method which creates FEC data for each scalable component independently. The proposed layered-LDGM codes support partial decoding and raise the probability of restoring the base component. These characteristics are very suitable for scalable video coding systems.