Muge Sayit

SDN for segment based flow routing of DASH

In this paper we propose an SDN based dynamic path selection for HTTP-based video streaming. MPEG-DASH is a recently proposed standard allowing rate adaptation over HTTP. On the other hand, Software Defined Networking (SDN) is a new network architecture, which allows determining routes of packet flows by an external controller software. In this study we develop an optimization model aiming to obtain maximum throughput for DASH services by selecting the optimal paths for video packet flows over SDN. The simulations show that the clients in the proposed system receive better QoE in terms of video bitrate, outage duration and startup delay when compared to the clients running in Internets best effort.

A hierarchical P2P clustering framework for video streaming systems

Abstract In this study, a novel overlay architecture for constructing hierarchical and scalable clustering of Peer-to-Peer (P2P) networks is proposed. The proposed architecture attempts to enhance the clustering of peers by incorporating join, split, merge and cluster leader election mechanisms in a fully distributed manner. It takes delay proximity of peers into account as distance measure. By constructing hierarchical clustering of peers, the control message overhead and maintenance such as host departure/host join overhead are decreased. Theoretical comparisons on overheads of the proposed system with that of other systems from literature are studied. The control mechanism for dynamic peer behavior of the architecture is tested over PlanetLab. The performance metrics used are end-to-end delay, diameter, cluster head distance, occupancy rate, peer join latency, accuracy and correctness. The test results are compared with Hierarchical Ring Tree (HRT) and mOverlay architecture. In addition, a P2P video streaming application is run over the proposed network overlay. Streaming tests show that video streaming applications perform well in terms of received video quality if hierarchical clusters considering delay proximity are used as underlying network architecture.

An SDN-assisted system design for improving performance of SVC-DASH

Today, the most of the video streaming system provides quality adaptation and prefers to send their packets over HTTP. MPEG group has standardized Dynamic Adaptive HTTP Streaming (DASH) regarding this tendency on the adaptive HTTP streaming. Besides providing quality adaptation with a non-scalable codec, DASH standard also allows Scalable Video Coding (SVC) to adapt quality. Software Defined Networks (SDN) is a recently emerged networking paradigm. SDN enables to separate control and data plane of computer networks and hence provides flexibility to network operators to implement their own routing approaches. In this paper, we propose a system for increasing Quality of Experience (QoE) of SVC-DASH clients by utilizing SDN. Our experimental results show that the proposed system provides an increase in received video quality and decrease in outage duration and startup delay when compared to the performance of the client running over todays Internet implementing shortest path routing.

Learning-based approach for layered adaptive video streaming over SDN

Software-defined networking is a recently emerging paradigm that decouples the control and data planes of computer networks. It allows for the implementation of application-specific routing algorithms, and the advantages that the SDN architecture enables can be used to enhance the performance of multimedia communication applications. In this paper, we propose an adaptive video streaming system with a learning-based approach, running over SDN. In the proposed video streaming system, we use a novel learning model to determine the optimal time to re-route the traffic flows and to change the bitrate of the video. The learning model aims to minimize the packet loss rate, quality changes and controller cost while adapting the flow routes and video quality. We have tested the performance of the learning-based approach by comparing it to traditional Internet routing and the greedy approach. The results show that the proposed system significantly outperforms the traditional Internet routing approach and the greedy approach in terms of quality of experience (QoE) and network cost under different network scenarios.

Software agents for peer-to-peer video streaming

Peer-to-peer (P2P) video streaming systems enable video data exchange between peers by reducing the overload of the servers while utilising network resources. Multi-agent systems (MASs), including many autonomous and intelligent software agents working on behalf of video peers, may also provide a feasible infrastructure for the implementation of P2P video streaming systems. Within this context, research on the use of software agents in video streaming systems has recently emerged. In this study, the authors discuss the development of an agent-based P2P video streaming system. Software engineering of the MAS with covering various aspects such as agent internals and interactions in the system is described. Performance evaluation of the proposed agent-based P2P system comparing with the popular in-use streaming application is also reported. Results show that a well-defined behaviour of a parent selection software agent can improve the continuity index in P2P video streaming systems. Therefore the users in the system can watch video in a better quality and lower end-to-end delay comparing with the currently used video streaming applications. They also examine that peer welcoming (traffic localisation) behaviour of the agents decreases the internal Internet service provider traffic significantly.

Parent Selection via Reinforcement Learning in Mesh-Based P2P Video Streaming

There are several successful deployments of peer to peer (P2P) video streaming systems which provide acceptable QoS. Researches on these systems continue to improve the experienced quality by system users. Since received video quality mostly depends on the parent selection, an efficient parent selection algorithm can increase the received video bitrate by peers and provide seamless streaming. In this paper, we propose a novel parent selection method based on reinforcement learning. By the proposed system model, the newly joined peer explores the peers in the system first, and uses this information for its further parent selection actions. We implemented our model on a Cool Streaming-like P2P video streaming system in ns3. Our results indicate that, selected parents by using reinforcement learning approach improve the playback continuity, with respect to parent selection method used by Cool Streaming. Furthermore, reinforcement learning approach helps peers to find more stable parents in case of peer churn.

Adaptive, incentive and scalable dynamic tree overlay for P2P live video streaming

In this paper, we propose a new multicast tree framework to be used in peer-to-peer (P2P) live video streaming systems. The proposed system, adapts the tree links under high peer churn and runs in a totally distributed manner. In order to provide this dynamism and seamless streaming at the same time, we propose a cross layer design involving scalable video codec, backup parents and hierarchical clusters. The performance of the system is measured in real world environment PlanetLab that has nodes distributed all over the world. The experiments show that the proposed system provides high quality of experience (QoE) in terms of Peak Signal to Noise Ratio (PSNR), playback delay and duration of pauses. The proposed system also provides incentive mechanism to its users.

P2P video streaming with ALTO protocol: A simulation study

With an increasing usage of P2P applications, an increase in Internet traffic is observed. One of the most important reason of this traffic is that P2P applications causes an extra load in backbones since network-awareness level of these applications are not at necessary level. In order to optimize network traffic, IETF ALTO WG has recently proposed a traffic localization protocol. This protocol provides to its users a ranking list considering network related parameters such as location, upload capacity, hop count and much more in order to provide reduction in backbone traffic. On the other hand, P2P video streaming applications require to assure an acceptable level of QoE, thus alto protocol usage in such systems need also consider QoE parameters besides traffic optimization. In this study, we present the effects of ALTO protocol implementation in P2P video streaming applications. We measured the performance in terms of QoE parameters in the ns-3 experiments of ALTO implementation in hybrid push-pull based systems. In the simulations, while a negligable decrease in continuity index is observed, a remarkable amount of decrease in ISP traffic and decrease in initial startup delay is observed.

Video-on-demand system architecture with ALTO-SDN integration

Software Defined Networking (SDN) is a promising technology for future internet applications through decoupling the data and control planes of computer networks. Enabling the development of application specific routing algorithms, the separation fosters the performance of internet applications. On the other hand, Application Layer Traffic Optimization (ALTO) provides network related information such as network paths and geographic locations of hosts to applications running on the internet. Thus, it is possible to maintain an increase in the performance of the end-to-end internet applications by integrating SDN technology and ALTO protocol. In this paper, we propose a Video-on-Demand (VoD) architecture utilizing the integration of SDN and ALTO. In the architecture, the clients running the VoD applications reside in an SDN domain while the servers remain out of the SDN domain. Simulation results show that the integration of SDN and ALTO increases the Quality of Experience (QoE) in a VoD system compared to QoE which is achieved in a traditional VoD architecture.

Parameter analysis for a push/pull-based P2P live video streaming application

In this paper, the impact of both the buffermap exchange period and partnership size of peers has been presented in a push/pull-based peer-to-peer (P2P) live video streaming application. The application has been implemented on network simulator-3 and the impact of aforementioned parameters on video streaming performance has been introduced via the simulation test results. The test results show that if the buffermap exchange period is fixed, received video quality and the control overhead increase with the increment in partnership size. On the other hand, if the partnership size of the nodes is fixed, a buffermap exchange period can be found for near-optimal video quality and control overhead.