Streaming In Wireless Networks Research Articles

Towards ubiquitous video services through scalable video coding and cross-layer optimization

Video content as one of the key features of future Internet services should be made ubiquitously available to users. Moreover, this should be done in a timely fashion and with adequate support for Quality of Service (QoS). Although providing the required coverage for ubiquitous video services, wireless networks, however, pose many challenges especially for QoS-sensitive video streaming due to their inadequate or varying capacity. In this article, we propose a cross-layer video adaptation solution, which may be used for optimizing network resource consumption and user experienced quality of video streaming in wireless networks; thus improving the availability of video services to mobile users. Our solution utilizes the flexibility of the Scalable Video Coding (SVC) technology and combines fast and fair Medium Access Control (MAC) layer packet scheduling with long-term application layer adaptation. The proposed solution both improves the usage of network resources by dropping video data based on its priority when the network is congested but also reduces efficiently the number of useless packet transfers in a congested network. We evaluate our solution with a simulation study under varying network congestion conditions. We find that already application layer adaptation gains over 60% less base layer losses, momentous for SVC video decodability and quality, than in the case without any adaptation. When our MAC layer scheduling is enabled, nearly a zero loss situation with respect to packet losses carrying base layers can be attained, resulting in peak-signal-to-noise ratio values very close to the original.

A framework for cross-layer optimization of video streaming in wireless networks

We present a general framework for optimizing the quality of video streaming in wireless networks that are composed of multiple wireless stations. The framework is general because: (i) it can be applied to different wireless networks, such as IEEE 802.11e WLAN and IEEE 802.16 WiMAX, (ii) it can employ different objective functions for the optimization, and (iii) it can adopt various models for the wireless channel, the link layer, and the distortion of the video streams in the application layer. The optimization framework controls parameters in different layers to optimally allocate the wireless network resources among all stations. More specifically, we address this video optimization problem in two steps. First, we formulate an abstract optimization problem for video streaming in wireless networks in general. This formulation exposes the important interaction between parameters belonging to different layers in the network stack. Then, we instantiate and solve the general problem for the recent IEEE 802.11e WLANs, which support prioritized traffic classes. We show how the calculated optimal solutions can efficiently be implemented in the distributed mode of the IEEE 802.11e standard. We evaluate our proposed solution using extensive simulations in the OPNET simulator, which captures most features of realistic wireless networks. In addition, to show the practicality of our solution, we have implemented it in the driver of an off-the-shelf wireless adapter that complies with the IEEE 802.11e standard. Our experimental and simulation results show that significant quality improvement in video streams can be achieved using our solution, without incurring any significant communication or computational overhead. We also explain how the general video optimization problem can be applied to other wireless networks, in particular, to the IEEE 802.16 WiMAX networks, which are becoming very popular.

Quality-aware bandwidth allocation for scalable on-demand streaming in wireless networks

In this paper, we propose a scalable transport scheme for delivering on-demand video streams over broadband wireless networks in next-generation network/IP multimedia subsystem (NGN/IMS) architecture. The proposed transport scheme makes use of fine-granular-scalability (FGS) encoded videos to accommodate high bandwidth variation of wireless networks. We formulate the bandwidth allocation to FGS-encoded streams as a resource allocation problem and develop a quality-aware bandwidth allocation scheme, called QABA. With QABA, the proposed transport scheme can dynamically adjust the bit rate allocated to different streams to maximize the overall perceptual quality when available network bandwidth varies with time. QABA is theoretically proven to be able to find the optimal bandwidth allocation for all on-demand streams. To validate the effectiveness of QABA, extensive trace-based simulations are performed.

Multi-Path Video Streaming in Wireless Networks using Time-Slot based Scheduling

This article proposes a scheme for scheduling real-time video packets through different paths in a QoS negotiation system, where active users have specific amounts of bandwidth negotiated with the network by each available interface. The considered QoS negotiation system implements a time-slot division strategy, to allocate the negotiated bandwidth to users. We claim that an efficient scheduling strategy is essential to exploit the features of mobile computers equipped with multiple wireless interfaces, which can be used simultaneously for transmission of data belonging to a single application, while minimizing the reordering delay at the receiver side due to transmission of data via multiple-paths with varying characteristics. A new scheduling mechanism is developed by taking into consideration such QoS systems. The effectiveness of the scheme is verified and compared with the most popular scheduling schemes through extensive simulations. The results demonstrate that our algorithm outperforms the former scheduling algorithms effectively.

Multicast video streaming for 4G wireless networks

AbstractA method for efficient video streaming in wireless networks is developed in this study. The proposed method is especially suitable for beyond 3G (B3G) wireless networks. It offers a significant increase in the number of clients that the system can potentially serve simultaneously as well as a significant reduction in the expected waiting time for a service. Under high load conditions, the ratio of the expected waiting time for a service offered by the proposed method to the expected waiting time offered by the conventional method currently used for video streaming in wireless networks is very significant and increases exponentially with the load. Copyright © 2007 John Wiley & Sons, Ltd.