When Video Streaming Meets Named Data Networking: A Case Study

Wang, Lijing; Moiseenko, Ilya; Wang, Dongsheng

doi:10.1109/hpcc-smartcity-dss.2016.0034

Cited by 3 publications

(5 citation statements)

References 6 publications

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“…To evaluate the performance of CBA and compare it with Throughput-based (TBA) and Buffer-based (BBA) adaptation peers, we emulate the two NDN topologies: the doubles 6 we use [x]+ to denote max{x, 0}. topology, shown in Fig.…”

Section: Evaluation Of Quality Adaptation In Ndnmentioning

confidence: 99%

“…The authors of [2] compare three state-of-the-art DASH adaptation algorithms over NDN and TCP/IP, finding NDN performance to notably exceed that of TCP/IP given certain network conditions. New adaptation algorithms specific to NDN have also been proposed, such as NDNLive [6], which uses a simple RTT mechanism to stream live content with minimal rebuffering.…”

Section: Related Workmentioning

confidence: 99%

“…2) Decline in quality: If the current segment is at a lower bitrate than the previous one, [v (a t−1 ) − v (a t )] + for two back to back segments 6 . 3) Rebuffer time: The amount of time spent with an empty buffer after choosing v (a t ).…”

Section: B Reward Formulation: Objective Qoementioning

confidence: 99%

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CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming

Alt

Ballard

Steinmetz

et al. 2019

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

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Recent advances in quality adaptation algorithms leave adaptive bitrate (ABR) streaming architectures at a crossroads: When determining the sustainable video quality one may either rely on the information gathered at the client vantage point or on server and network assistance. The fundamental problem here is to determine how valuable either information is for the adaptation decision. This problem becomes particularly hard in future Internet settings such as Named Data Networking (NDN) where the notion of a network connection does not exist.In this paper, we provide a fresh view on ABR quality adaptation for QoE maximization, which we formalize as a decision problem under uncertainty, and for which we contribute a sparse Bayesian contextual bandit algorithm denoted CBA. This allows taking high-dimensional streaming context information, including client-measured variables and network assistance, to find online the most valuable information for the quality adaptation. Since sparse Bayesian estimation is computationally expensive, we develop a fast new inference scheme to support online video adaptation. We perform an extensive evaluation of our adaptation algorithm in the particularly challenging setting of NDN, where we use an emulation testbed to demonstrate the efficacy of CBA compared to state-of-the-art algorithms.

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Section: Evaluation Of Quality Adaptation In Ndnmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming

Alt

Ballard

Steinmetz

et al. 2019

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

View full text Add to dashboard Cite

show abstract

“…Most of the aforementioned DASH-based video streaming proposals for ICN consider the existence of a single path connecting the sources with the clients [6], [14], [15]. This is sub-optimal, as not all the paths connecting the client with the sources are exploited, hence, limiting the resources that the client can use to adapt the video streaming towards a high quality.…”

Section: Related Workmentioning

confidence: 99%

“…The similarities in the content retrieval mechanisms of DASH and NDN have attracted the attention of the research community [3], [6], [14], [15]. Detti et al [14] proposed a cooperative adaptive video streaming application for CCN.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Video Streaming With Network Coding Enabled Named Data Networking

Saltarin

Bourtsoulatze

Thomos

et al. 2017

IEEE Trans. Multimedia

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Abstract-The fast and huge increase of Internet traffic motivates the development of new communication methods that can deal with the growing volume of data traffic. To this aim, Named Data Networking (NDN) has been proposed as a future Internet architecture that enables ubiquitous in-network caching and naturally supports multi-path data delivery. Particular attention has been given to using Dynamic Adaptive Streaming over HTTP (DASH) to enable video streaming in NDN as in both schemes data transmission is triggered and controlled by the clients. However, state-of-the-art works do not consider the multipath capabilities of NDN and the potential improvements that multipath communication brings, such as increased throughput and reliability, that are fundamental for video streaming systems. In this paper, we present a novel architecture for dynamic adaptive streaming over network coding enabled NDN. In comparison to previous works proposing dynamic adaptive streaming over NDN, our architecture exploits network coding to efficiently use the multiple paths connecting the clients to the sources. Moreover, our architecture enables efficient multi-source video streaming and improves resiliency to Data packet losses. The experimental evaluation shows that our architecture leads to reduced data traffic load on the sources, increased cache-hit rate at the innetwork caches and faster adaptation of the requested video quality by the clients. The performance gains are verified through simulations in a Netflix-like scenario.

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Performance Evaluation of Video Streaming Application via Named Data Network (NDN)

Rukmana

Sari

2019

2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)

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When Video Streaming Meets Named Data Networking: A Case Study

Cited by 3 publications

References 6 publications

CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming

CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming

Adaptive Video Streaming With Network Coding Enabled Named Data Networking

Performance Evaluation of Video Streaming Application via Named Data Network (NDN)

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