Towards QoS-aware routing for DASH utilizing MPTCP over SDN

Herguner, Korhan; Kalan, Reza Shokri; Çetinkaya, Cihat; Sayıt, Müge

doi:10.1109/nfv-sdn.2017.8169844

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…Therefore, methods that use variations at the transport level show an improvement in the overall QoE in DASH. For instance, the authors of [23,24] used Multipath TCP (MPTCP) [25], an extension of TCP, to transmit subflows of DASH streams over multiple paths. The results were significantly better than using single TCP connections.…”

Section: Non-tcp-based Sdn Solutions For Dashmentioning

confidence: 99%

“…The mapping process from a user HTTP request to a path is shown in the dotted region in Figure 2. One of the most essential processes is the calculation of the user category, which can be done using various approaches, from advanced Machine Learning (ML) or other Artificial Intelligence (AI) as done by Bentaleb et al [22], to other optimization heuristics as done by Herguner et al [23]. However, for simplicity, in the current implementation, we attach this value as a parameter on the User Profile, leaving a more elaborate selection process as future work.…”

Section: An Overview Of Sand/3mentioning

confidence: 99%

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SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

et al. 2019

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Dynamic Adaptive Streaming over HTTP (DASH) is a widely used standard for video content delivery. Video traffic, most of which is generated from mobile devices, is shortly to become the most significant part of Internet traffic. Current DASH solutions only consider either client-or server-side optimization, leaving other components in DASH (e.g., at the transport layer) to default solutions that cause a performance bottleneck. In that regard, although it is assumed that HTTP must be necessarily transported on top of TCP, with the latest introduction of HTTP/3, it is time to re-evaluate its effects on DASH. The most substantial change in HTTP/3 is having Quick UDP Internet Connections (QUIC) as its primary underlying transport protocol. However, little is still know about the effects on standard DASH client-based adaption algorithms when exposed to the future HTTP/3. In this paper, we present SAND/3, an SDN (Software Defined Networking)-based Quality of Experience (QoE) control method for DASH over HTTP/3. Since the official deployment of HTTP/3 has not been released yet, we used the current implementation of Google QUIC. Preliminary results show that, by applying SAND/3, which combines information from different layers orchestrated by SDN to select the best QoE, we can obtain steadier media throughput, reduce the number of quality shifts in at least 40%, increase the amount downloaded content at least 20%, and minimize video interruptions compared to the current implementations regardless of the client adaption algorithm.

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Section: Non-tcp-based Sdn Solutions For Dashmentioning

confidence: 99%

Section: An Overview Of Sand/3mentioning

confidence: 99%

SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

et al. 2019

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“…Many scholars around the world conduct the research and implementation of MPLS technology [5][6][7][8][9][10][11]. For example, [12] developed an analytical model of successive queues that describes the tunneling mechanism in the MPLS network.…”

Section: Review Of Performed Studiesmentioning

confidence: 99%

Distribution of information flows in the advanced network of MPLS of railway transport by means of a neural model

et al. 2019

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Ensuring interoperability of railway transport is possible only due to the developed information structure. Today, Ukraine uses the information-telecommunication system (ITS) of railway transport, which is based on a data communication network. The effectiveness of its work is largely determined by the routing system. The current algorithm for choosing the shortest route, which is used in the existing routing protocol (OSPF), does not always lead to an effective result. However, there is MPLS technology, which could improve the quality of the ITS network by creating virtual channels between its nodes. The authors proposed a scheme for selecting tunnels for the flows in the MPLS network, which is based on the neural model of a multilayer perceptron of configuration 18–3–3–10 with the activation function Softmax in hidden layers and a linear activation function in the input layer. To simulate the network operation, flow data is needed: class of service (CoS), sender and recipient identifiers, average flow rate vector and tunnel data (their initial load). The final load of the tunnels is taken as the resulting output of the neural network, on the basis of which the tunnel is selected for the flow of the k-th class of service.

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“…The solution to this problem is possible with the use of new transport technologies; in particular, the multiprotocol switching technology using labels (Multiprotocol Label Switching, MPLS) on the one hand, and the use of neural network technologies, on the other hand [3]. The characteristics of MPLS [1,[5][6][7] on the basis of analytical and simulation models were highlighted by the modern scientists such as Budyldina N.V., Goldstein A.B., Olifer V.G., Pasko S.P., Romanov O.I., Rukkas K.M., Sharadka A.M., Zaichenko O.Yu., Zaitsev D.A. and others.…”

Section: Introductionmentioning

confidence: 99%

Использование Нейросетевых Технологий В Формировании Исследовательской Компетентности Ит-Специалистов Железнодорожной Отрасли По Ступенчатой подготовкой

Бондарева¹,

Мирошниченко²,

Пахомова³

et al. 2018

SWJ

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У статті висвітлено питання розробки методики формування дослідницької компетентності з використанням нейромережних технологій у ступеневій підготовці ІТ-фахівців залізничної галузі. Запропонована методика «ResCompStageNNT» складається з таких етапів: виз

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Towards QoS-aware routing for DASH utilizing MPTCP over SDN

Cited by 12 publications

References 18 publications

SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

Distribution of information flows in the advanced network of MPLS of railway transport by means of a neural model

Использование Нейросетевых Технологий В Формировании Исследовательской Компетентности Ит-Специалистов Железнодорожной Отрасли По Ступенчатой подготовкой

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Towards QoS-aware routing for DASH utilizing MPTCP over SDN

Cited by 12 publications

References 18 publications

SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

SAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3

Distribution of information flows in the advanced network of MPLS of railway transport by means of a neural model

Использование Нейросетевых Технологий В Формировании Исследовательской Компетентности Ит-Специалистов Железнодорожной Отрасли По Ступенчатой ​​подготовкой

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Использование Нейросетевых Технологий В Формировании Исследовательской Компетентности Ит-Специалистов Железнодорожной Отрасли По Ступенчатой подготовкой