Burak Gorkemli

Scalable video streaming over OpenFlow networks: An optimization framework for QoS routing

OpenFlow is a clean-slate Future Internet architecture that decouples control and forwarding layers of routing, which has recently started being deployed throughout the world for research purposes. This paper presents an optimization framework for the OpenFlow controller in order to provide QoS support for scalable video streaming over an OpenFlow network. We pose and solve two optimization problems, where we route the base layer of SVC encoded video as a lossless-QoS flow, while the enhancement layers can be routed either as a lossy-QoS flow or as a best effort flow, respectively. The proposed approach differs from current QoS architectures since we provide dynamic rerouting capability possibly using non-shortest paths for lossless and lossy QoS flows. We show that dynamic rerouting of QoS flows achieves significant improvement on the videos overall PSNR under network congestion.

A QoS-enabled OpenFlow environment for Scalable Video streaming

This paper describes an architecture to support QoS flows in an OpenFlow environment with a centralized ‘controller’ and many ‘forwarders.’ The paper primarily focuses on the analytical framework for optimization of the QoS flow routing, and the functionality needed within the controller and forwarders to efficiently support QoS. We also describe the control layer messaging between the controller and forwarder to set up queues, detect congestion and reroute traffic streams that require QoS. We provide some experimental results to route Scalable Video Coding (SVC) encoded video comprised of a base layer, which requires error free decoding and hence QoS, and one or more enhancement layers, which are error resilient and hence generate best effort traffic.

Video streaming over wireless DCCP

It is envisioned that access networks will be mostly wireless in the future. Hence, it is of interest to consider extensions of the datagram congestion control protocol (DCCP) for wireless networks. This paper focuses on the problems of video streaming over DCCP in the wireless domain and proposes a cross-layer solution in which the wireless packet loss information available in the medium access (MAC) layer is utilized by DCCP to distinguish congestion losses from wireless losses and behave accordingly. Tests performed with our modified DCCP confirm that using cross-layer loss information prevents unnecessary rate decreases and results in better video streaming experiences.

Effects of MGS fragmentation, slice mode and extraction strategies on the performance of SVC with medium-grained scalability

This paper presents a comparison of a wide set of MGS fragmentation configurations of SVC in terms of their PSNR performance, with the slice mode on or off, using multiple extraction methods. We also propose a priority-based hierarchical extraction method which outperforms other extraction schemes for most MGS configurations. Experimental results show that splitting the MGS layer into more than five fragments, when the slice mode is on, may result in noticeable decrease in the average PSNR. It is also observed that for videos with large key frame enhancement NAL units, MGS fragmentation and/or slice mode have positive impact on the PSNR of the extracted video at low bitrates. While using slice mode without MGS fragmentation may improve the PSNR performance at low rates, it may result in uneven video quality within frames due to varying quality of slices. Therefore, we recommend combined use of up to five MGS fragments and slice mode, especially for low bitrate video applications.

Adaptive Streaming Of Scalable Stereoscopic Video Over DCCP

We propose a new adaptive streaming model that utilizes DCCP in order to efficiently stream multi-view video over the Internet for 3DTV transport. The model effectively allocates the available channel bandwidth, which is calculated by DCCP, among the views. The video rate is adapted to the DCCP rate for each group of pictures (GoP) by adaptive extraction of layers from a scalable multi-view bitstream. The objective of the streaming model is to maximize perceived quality of the received 3D video while minimizing the number of possible display interrupts. Experimental results successfully demonstrate stereo video streaming over DCCP on wide area network.

Adaptation strategies for streaming SVC video

This paper aims to determine the best rate adaptation strategy to maximize the received video quality when streaming SVC video over the Internet. Different bandwidth estimation techniques are implemented for different transport protocols, such as using the TFRC rate when available or calculating the packet transmission rate otherwise. It is observed that controlling the rate of packets dispatched to the transport queue to match the video extraction rate resulted in oscillatory behavior in DCCP CCID3, decreasing the received video quality. Experimental results show that video should be sent at the maximum available network rate rather than at the extraction rate, provided that receiver buffer does not overflow. When the network is over-provisioned, the packet dispatch rate may also be limited with the maximum extractable video rate, to decrease the retransmission traffic without affecting the received video quality.

SVC Coded Video Streaming over DCCP

The datagram congestion control protocol (DCCP) is designed to be a replacement for the user datagram protocol (UDP) that is used for media delivery, with congestion control identifier 3 (CCID3) tailored for video streaming applications. In this paper, we investigate the methods of streaming video, which is coded with the scalable video coding (SVC) extension of H.264/AVC, over the transmission control protocol (TCP) and DCCP (using CCID3), and try to come up with a solution such that the quality of the received video is maximized while both the number and the length of buffering events are minimized

Adaptive Streaming of Scalable Stereoscopic Video Over DCCP

We propose a new adaptive streaming model that utilizes DCCP in order to efficiently stream stereoscopic video over the Internet for 3DTV transport. The model allocates the available channel bandwidth, which is calculated by the DCCP, among the views according to the suppression theory of human vision. The video rate is adapted to the DCCP rate for each group of pictures (GoP) by adaptive extraction of layers from a scalable multi-view bitstream. The objective of the streaming model is to maximize perceived quality of the received 3D video while minimizing the number of possible display interrupts. Experimental results successfully demonstrate stereo video streaming over DCCP on wide area network.

Adaptation strategies for MGS scalable video streaming

An adaptive streaming framework consists of a video codec that can produce video encoded at a variety of rates, a transport protocol that supports an effective rate/congestion control mechanism, and an adaptation strategy in order to match the video source rate to the available network throughput. The main parameters of the adaptation strategy are encoder configuration, video extraction method, determination of video extraction rate, send rate control, retransmission of lost packets, decoder buffer status, and packetization method. This paper proposes optimal adaptation strategies, in terms of received video quality and used network resources, at the codec and network levels using a medium grain scalable (MGS) video codec and two transport protocols with built-in congestion control, TCP and DCCP. Key recommendations are presented to obtain the best results in adaptive video streaming using TCP or DCCP based on extensive experimental results over the Internet.

Dynamic management of control plane performance in software-defined networks

The controller or the “control plane” is at the heart of software defined networks (SDN). As SDN migrates to wide area networks (WAN), scalability and performance are two important factors that differentiate one controller from another, and they are critical for success of SDN for end-to-end service management. We distinguish control flows from data flows, and introduce a novel dynamic control plane architecture to distribute different control flows among multiple controller instances depending on specific controller load and controller processor utilization or on the data flow service type. We propose “control flow tables”-a concept introduced in this paper-that are embedded in OpenFlow flow tables to distribute the control flows among various controller instances. Experimental results demonstrate the improvements in the data plane service performance as a result of the proposed control flow management procedures when the bottleneck is the controller CPU or throughput of links between the controller and switches.