Cihat Cetinkaya

Bio: Cihat Cetinkaya is an academic researcher from Ege University. The author has contributed to research in topics: Software-defined networking & Dash. The author has an hindex of 6, co-authored 18 publications receiving 121 citations. Previous affiliations of Cihat Cetinkaya include Muğla University.

SDN for segment based flow routing of DASH

Abstract: 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 Internet's best effort.

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

Abstract: 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.

Towards QoS-aware routing for DASH utilizing MPTCP over SDN

Abstract: Multipath TCP (MPTCP) has gained great attention by the researchers and network application developers due to its features providing better bandwidth utilization and higher reliability recently. Utilizing MPTCP in the datacenters provides performance gain to the applications. If the underlying network has Software Defined Networking (SDN) architecture, the routing of the MPTCP subflows can be specialized. In this paper, we propose an architecture utilizing MPTCP in an SDN-based ISP in order to serve guaranteed services to the video streaming clients. The number of MPTCP subflows and routes of the subflows are determined based on a mixed integer linear programming model. The simulation results show that the proposed architecture provides increase in received throughput and decrease in duration of outages when it is compared to a general-purposed throughput maximization approach.

Design of a layer-based video streaming system over software-defined networks

Abstract: Software Defined Networking (SDN) technology provides flexibility in routing of flows by separating data and control plane of computer networks. In addition to that, realtime traffic information can be inferred by using SDN. The advantages offered by SDN technology can be utilized to enhance the performance of network applications such as video streaming systems. In this paper, we propose a layered video streaming system to provide an increase in the performance achieved by video streaming clients running in an SDN domain. SDN controller runs an optimization algorithm that determines optimal video codec type and the number of layers based on the network conditions. Hence, the clients are directed to select appropriate video codec under the constraint of measured network conditions by SDN controller. We tested the performance of the proposed system by comparing with different approaches. The simulation results show that the performance of the proposed system outperforms the traditional best effort approach.

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

Abstract: The highly demanding Over-The-Top (OTT) multimedia applications pose increased challenges to Internet Service Providers (ISPs) for assuring a reasonable Quality of Experience (QoE) to their customers due to lack of flexibility, agility and scalability in traditional networks. The future networks are shifting towards the cloudification of the network resources via Software Defined Networks (SDN) and Network Function Virtualization (NFV). This will equip ISPs with cutting-edge technologies to provide service customization during service delivery and offer QoE which meets customers’ needs via intelligent QoE control and management approaches. Towards this end, we provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high-level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview

Abstract: Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey.

Abstract: We provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

Quality of Experience-Centric Management of Adaptive Video Streaming Services: Status and Challenges

Abstract: Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming (HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users’ QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users’ QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users’ QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server- and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years.