Chi-Huang Shih

A self-regulated redundancy control scheme for wireless video transmission

This paper presents a self-regulated redundancy control scheme for high-bit-rate video transmission using packet-level forward-error-correction (FEC) codes over error-prone wireless networks. The effectiveness of FEC on video is obtained by regulating its redundancy cost to balance that tradeoff of bandwidth utilization and FEC efficiency based on channel status, temporal dependency of video frames, and network congestion level. Experimental results show the proposed scheme maintains the desired quality-of-service (QoS) control over unloaded networks with the realistically measured wireless loss trace in 802.11b WLAN and over loaded networks, the adverse effect of FEC efficiency due to blindly increasing redundancy can be reduced to achieve the better video quality.

Secure and Reliable IPTV Multimedia Transmission Using Forward Error Correction

With the wide deployment of Internet Protocol (IP) infrastructure and rapid development of digital technologies, Internet Protocol Television (IPTV) has emerged as one of the major multimedia access techniques. A general IPTV transmission system employs both encryption and forward error correction (FEC) to provide the authorized subscriber with a high-quality perceptual experience. This two-layer processing, however, complicates the system design in terms of computational cost and management cost. In this paper, we propose a novel FEC scheme to ensure the secure and reliable transmission for IPTV multimedia content and services. The proposed secure FEC utilizes the characteristics of FEC including the FEC-encoded redundancies and the limitation of error correction capacity to protect the multimedia packets against the malicious attacks and data transmission errors/losses. Experimental results demonstrate that the proposed scheme obtains similar performance compared with the joint encryption and FEC scheme.

Multiple-Instance Learning via Decision-Based Neural Networks

Multiple Instance Learning (MIL) is a variation of supervised learning, where the training set is composed of many bags, each of which contains many instances. If a bag contains at least one positive instance, it is labelled as a positive bag; otherwise, it is labelled as a negative bag. The labels of the training bags are known, but that of the training instances are unknown. In this paper, a Multiple Instance Decision Based Neural Networks (MI-DBNN) is proposed for MIL, which employs a novel discriminate function to capture the nature of MIL. The experiments were performed on MUSK1 and MUSK2 data sets. In comparison with other methods, MI-DBNN demonstrates competitive classification accuracy on MUSK1 and MUSK2 data sets, which are 97.8% and 98.4%, respectively.

Adaptive Forward Error Correction Combined with Packet Size Control for Wireless Video

We consider a scenario where multiple pairs of users exchange information within pair, with the help of a dedicated multi-antenna relay. The protocol integrates the idea of analogue network coding in mixing two data streams originating from the same user pair, together with the spatial multiplexing of the data streams originating from different user pairs. The key feature of the protocol is that it enables both the relay and the users to participate in interference cancellation. We propose several beamforming schemes for the multi-antenna relay and evaluate the performance using information theoretical metrics such as ergodic capacity, outage probability and diversity and multiplexing tradeoff. Analytical and simulation results justify that the ergodic capacity, outage probability and diversity and multiplexing tradeoff of the proposed beamforming schemes outperform comparable schemes.Forward error correction (FEC) is one popular error control technique to protect the video bitstream by encoding the redundancies to recover the source information errors/losses. However, the FEC redundancy trades additional bandwidth consumption to protect video data, and therefore he wireless channel properties such as burst errors and limited bandwidth impair the FEC efficiency. In this paper, we couple the packet size control mechanism with the FEC echnique to enhance the FEC efficiency in the wirelessworks. Accordingly, an adaptive FEC scheme combined with packet size control is developed to simultaneously adjust the transport packet size and the degree of FEC redundancy based on the least bandwidth consumption strategy. The experimental results show that compared to the traditional adaptive FEC scheme, the proposed scheme can achieve a PSNR gain of 1.17dB and decrease as much as 52% of bandwidth consumption.

A transparent QoS mechanism to support IntServ/DiffServ networks

IntServ and DiffServ networks are both proposed to promote quality of service (QoS) for multimedia applications in the Internet. However, the complexity of communication between diverse applications and underlying QoS architectures leads to one of the deployment problems which decreases the utility of QoS provisioning. Without modifying legacy applications, the paper presents a transparent QoS mechanism (TQM) to communicate with underlying QoS architectures and also provide swappable modules to support different QoS setups for diverse applications. Currently, TQM is implemented on the UNIX platform, and some important issues of applying TQM in IntServ/DiffServ networks have been examined.

Small-block interleaving for low-delay cross-packet forward error correction over burst-loss channels

By adding the redundant packets into source packet block, cross-packet forward error correction FEC scheme performs error correction across packets and can recover both congestion packet loss and wireless bit errors accordingly. Because cross-packet FEC typically trades the additional latency to combat burst losses in the wireless channel, this paper presents a FEC enhancement scheme using the small-block interleaving technique to enhance cross-packet FEC with the decreased delay and improved good-put. Specifically, adopting short block size is effective in reducing FEC processing delay, whereas the corresponding effect of lower burst-error correction capacity can be compensated by deliberately controlling the interleaving degree. The main features include i the proposed scheme that operates in the post-processing manner to be compatible with the existing FEC control schemes and ii to maximize the data good-put in lossy networks; an analytical FEC model is built on the interleaved Gilbert-Elliott channel to determine the optimal FEC parameters. The simulation results show that the small-block interleaved FEC scheme significantly improves the video streaming quality in lossy channels for delay-sensitive video. Copyright

A Transparent Loss Recovery Scheme Using Packet Redirection for Wireless Video Transmissions

With the wide deployment of wireless networks and the rapid integration of various emerging networking technologies nowadays, Internet video applications must be updated on a sufficiently timely basis to support high end-to-end quality of service (QoS) levels over heterogeneous infrastructures. However, updating the legacy applications to provide QoS support is both complex and expensive since the video applications must communicate with underlying architectures when carrying out QoS provisioning, and furthermore, should be both aware of and adaptive to variations in the network conditions. Accordingly, this paper presents a transparent loss recovery scheme to transparently support the robust video transmission on behalf of real-time streaming video applications. The proposed scheme includes the following two modules: (i) a transparent QoS mechanism which enables the QoS setup of video applications without the requirement for any modification of the existing legacy applications through its use of an efficient packet redirection scheme; and (ii) an instant frame-level FEC technique which performs online FEC bandwidth allocation within TCP-friendly rate constraints in a frame-by-frame basis to minimize the additional FEC processing delay. The experimental results show that the proposed scheme achieves nearly the same video quality that can be obtained by the optimal frame-level FEC under varying network conditions while maintaining low end-to-end delay.

Real-time video streaming using prediction-based forward error correction

Real-time video streaming applications typically use an on-line forward error correction (FEC) technique to recover transmission losses with a low delay overhead. However, transmitting prioritized video data over variable-rate transmission channels complicates the FEC rate allocation process. Specifically, on-line FEC schemes result in an inefficient utilization of the available FEC bandwidth in the absence of prior information regarding the statistics of video traffic. In most streaming networks, the optimal FEC configuration is computed off-line in accordance with an analytical model. However, the present study proposes an on-line FEC scheme in which real-time FEC allocation is performed by extending the analytical FEC model with the frame size prediction technique. In the proposed approach, the optimal FEC configuration is computed in advance on a frame-by-frame basis over a series of predicted video frames, thereby yielding a significant reduction in the data buffering delay. The performance effects of frame-size prediction errors are mitigated by continuously revising the FEC configuration each time a new frame arrives. Moreover, a transmission rate control mechanism is proposed to ensure that each video frames satisfies its presentation deadline. The simulation results show that the proposed prediction-based FEC scheme minimizes the FEC processing delay while achieving virtually the same perceived video quality as that obtained using the off-line optimal FEC model.

A Fast and Efficient FEC Enhancement Scheme for Delay-Sensitive Video Transmissions

In end-to-end networks, the burst losses caused by network congestion and wireless channel errors reduce the efficiency of the forward error correction (FEC) scheme. Although different control techniques are designed to enhance the loss recovery ability, the resulting FEC processing latencies may increase the end-to-end delay to violate the stringent constraints of delay sensitive video communications. Therefore, this paper presents a FEC enhancement scheme to achieve a tradeoff between end-to-end delay and the FEC loss recovery performance. The proposed scheme consists of 1) an adaptive block size control mechanism to reduce the FEC processing delay and 2) the interleaving technique to improve the error correction capacity of small block sizes. The experimental results show that the proposed scheme significantly improves the video streaming quality in lossy channels for delay-sensitive video.The wide scale deployment of cooperative vehicular ad-hoc networks will require the design of efficient congestion control policies that guarantee stable and reliable communications between vehicles and with infrastructure nodes. These policies should reduce the load on the communications channel, while satisfying the strict applications reliability requirements. To this aim, this letter proposes and evaluates a contextual cooperative congestion control policy that exploits the traffic context information of each vehicle to reduce the channel load, while satisfying the vehicular applications requirements.

Sliding-window forward error correction using Reed-Solomon code and unequal error protection for real-time streaming video

Summary Forward error correction (FEC) techniques are widely used to recover packet losses over unreliable networks in real-time video streaming applications. Traditional frame-level FEC encodes 1 video frame in each FEC coding window. By contrast, in the expanding-window FEC scheme, high-priority frames are included in the FEC processing of the following frames, so as to construct a larger coding window. In general, expanding-window FEC improves the recovery performance of FEC, because the high-priority frame can be protected by multiple windows and the use of a larger coding window increases the efficiency. However, the larger window size also increases the complexity of the coding and the memory space requirements. Consequently, expanding-window FEC is limited in terms of practical applications. Sliding-window FEC adopts a fixed window size in order to approximate the performance of the expanding-window FEC method, but with a reduced complexity. Previous studies on sliding-window FEC have generally adopted an equal error protection (EEP) mechanism to simplify the analysis. This paper considers the more practical case of an unequal error protection (UEP) strategy. An analytical model is derived for estimating the playable frame rate (PFR) of the proposed sliding-window FEC scheme with a Reed-Solomon erasure code for real-time non-scalable streaming applications. The analytical model is used to determine the optimal FEC configuration which maximizes the PFR value under given transmission rate constraints. The simulation results show that the proposed sliding-window scheme achieves almost the same performance as the expanding-window scheme, but with a significantly lower computational complexity.