International audienceNowadays, Internet video is the dominant internet traffic. DASH is an adaptive video streaming technique introduced to enable high quality video delivery over HTTP. In home networks, multiple video streams will compete for bandwidth, thus leading to poor performance and impacting the received quality of experience. In this paper we introduce a new technique to address this issue at the home network gateway without modifying neither the client player nor the video server. We design our framework NAVS (Network Assisted Video Streaming) relies on the deployment of Software Defined Networking (SDN). NAVS performs a dynamic traffic shaping based on the collected network traffic statistics and monitoring of video flows. NAVS dynamically allocates bandwidth for each video flow in real time. NAVS scheme has been evaluated over several metrics: bandwidth utilization, instability of players as well as the average video quality received by the clients. Our results demonstrate an improvement for all these parameters

Adaptive video streaming techniques were introduced to enable high quality video delivery over HTTP. These schemes propose to choose dynamically the appropriate video rate to match the operating conditions. In home networks, wireless access is the predominant Internet access. Multiple clients/players with different link qualities compete over a limited wireless bandwidth to transfer their video streams. As a result, some users undergo unpredictable degradations of their Quality of Experience (QoE) while others benefit from these perturbations. In this paper we introduce a new technique to address this issue at the gateway without modifying neither the client nor the video server side. We design a framework WNAVS (Wireless Network Assisted Video Streaming) that relies on the deployment of Software Defined Networking (SDN). WNAVS performs a dynamic traffic shaping based on collected network traffic statistics and allocates bandwidth for the clients in real time. We evaluate WNAVS over several metrics: fairness, instability, average video quality as well as the video traffic utilization. Our results demonstrate an improvement for all these parameters.

The IEEE 802.16 standard, which is called Worldwide Interoperability for Microwave Access (WiMAX) is a low cost solution for Internet access in metropolitan and rural areas; it provides both high throughput and large coverage broadband wireless access. Although it defines five service level classes to support real-time and bandwidth demanding applications, each class is associated with a set of Quality of Service (QoS) parameters. However, the standard does not specify which scheduling algorithm should be used to serve packets. Due to the wireless channel variability, scheduling mechanisms widely studied for wired networks are not suitable for IEEE 802.16 networks. In this paper, we introduce Deadline maximum Signal to Interference Ratio scheduler , which makes bandwidth allocation decisions based on information about the channel quality and deadline. Simulation results show the proposed approach gains more delivering packet and decreases the average end to end delay and improve the fairness index.

Dynamic Adaptive Streaming over HTTP (DASH) was introduced to enable high video quality streaming over HTTP. DASH depends on the adaptation logic at the client to choose which video bitrate to stream from the content server for each chunk. For clients receiving video over a cellular network, the cellular first hop tends to be the bandwidth bottleneck and can exhibit significant swings in available bandwidth. In this paper we develop and evaluate a Dynamic Adaptation for mobile Video Streaming (DAVS), a technique that can be used within DASH adaptation to handle the significant bandwidth variability experienced by cellular mobile clients. In our scheme the main innovation is that the client chooses a bitrate based on whether the playout buffer occupancy (BO) falls below or above a dynamic threshold. In addition, the scheme attempts to minimize bitrate switching by again delaying a change of video bitrate selection by a window of time -that is also dynamically determined. We evaluate the performance of DAVS over real traces collected from a mobile network operator. DAVS shows better performance over different video streaming metrics. Furthermore, It increases the QoE by a range 15% -55% compared to benchmark algorithms.

To satisfy the need for ubiquitous connectivity of their customers, many enterprises (e.g., hotels, cafes and commercial centers) deploy EWLAN (Enterprise WLAN). In these networks, video streaming is both one of the most popular and challenging applications. To improve the overall users QoE in EWLAN, we propose to address simultaneously the resource bottlenecks that can occur on wireless links as well as the lack of overall bandwidth that can be experienced on the Internet access link. We propose a dynamic video Streaming Management based on software defined enterprIse wireLEss LANs (SMILE), an SDN framework which dynamically allocates the bandwidth among different access points based on their workloads and on the available bandwidth. We evaluate SMILE over several adaptive video streaming performance metrics: instability, rebuffering, and average video quality. The results demonstrate an improvement for these parameters with different adaptation logic's when SMILE is in use.