Towards SVC-based Adaptive Streaming in information centric networks

Petrangeli, Stefano; Bouten, Niels; Claeys, Maxim; Turck, Filip De

doi:10.1109/icmew.2015.7169859

Cited by 22 publications

(15 citation statements)

References 9 publications

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“…If the buffer evolution is more rapid, the heuristic switches to a panic mode when the buffer is lower than B lower . The result is that the quality of the next segment is set to the lowest possible and the heuristic returns to the buffering state (lines [21][22][23]. Note that the algorithm compares with the lower threshold B lower and not with the panic threshold B panic as it detects a rapid change in the buffer state.…”

Section: Basic Quality Selection Heuristicmentioning

confidence: 99%

Clustering‐based quality selection heuristics for HTTP adaptive streaming over cache networks

et al. 2018

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HyperText Transfer Protocol (HTTP) Adaptive Streaming (HAS) has become the de facto standard video-streaming technology. The benefits of HAS are manifold: reliable transmission of video data avoiding artifacts caused by packet loss, easy fire wall, and Network Address Translation (NAT) traversal and the seamless reuse of existing HTTP caching infrastructure. However, introducing transparent, intermediary caching nodes on the delivery path can impact the Quality of Experience (QoE) perceived by the end user. In cache-assisted HAS, segments can be served from different origins based on the content of the caches, causing highly fluctuating throughput and Round-Trip Time (RTT) measurements, negatively impacting the stability and optimality of the quality decisions due to incorrect throughput estimations. In this paper, we propose heuristics that are able to use information on the streaming origin and intermediary cache contents to optimize the quality selection process. Using more accurate per origin throughput measurements, buffer starvations can be avoided. Moreover, including the cache state information in the decision process can positively impact the streaming quality. Furthermore, approximation techniques based on unsupervised incremental clustering are proposed to detect the streaming origin in absence of an external information channel. Similarly, a cache probability-based heuristic is proposed to predict the content of the expected delivery location when this information is not transferred. With perfect information, the proposed heuristics improve the QoE with 0.52 on a scale between 1 and 5, while the approximation techniques result in a performance gain between 0.04 and 0.36 for a dynamic scenario and a reduction of buffer starvations with a factor 3 to 7.

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Section: Basic Quality Selection Heuristicmentioning

confidence: 99%

Clustering‐based quality selection heuristics for HTTP adaptive streaming over cache networks

et al. 2018

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“…One possible solution is to use purely buffer-based rate adaptation heuristics, in which only the buffer filling is used to decide upon the next segment and quality to download. One such example is the SVC Backfilling heuristic, proposed by Petrangeli et al [26]. In this heuristic, the client always checks whether or not all base layers have been downloaded.…”

Section: B Rate Adaptation Heuristicsmentioning

confidence: 99%

“…In this paper, we focus on two rate adaptation heuristics: SVC-Cursor and SVC-Backfilling [11], [26]. These heuristics are briefly discussed below, along with the changes required to realize the push-based approach presented in Section III-A.…”

Section: B Rate Adaptation Heuristicsmentioning

confidence: 99%

An HTTP/2 push-based approach for SVC adaptive streaming

Hooft

Petrangeli

Bouten

et al. 2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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Abstract-HTTP Adaptive Streaming (HAS) is the de facto standard for over-the-top video streaming. In HAS, video content is encoded at multiple quality levels and temporally divided into multiple segments. The client can select the quality level for every video segment, allowing smoother playback and a better Quality of Experience (QoE). Although results are promising, current solutions often suffer from high round-trip time (RTT) cycles in mobile networks. This is especially true for scalable video coding (SVC), where multiple requests are required to retrieve a single video segment. Meanwhile, the IETF has standardized the HTTP/2 protocol since February 2015, providing new features that allow a reduction of the page load time in web browsing. In this paper, we propose a novel approach based on HTTP/2's server push feature to actively push the base layer of live, SVCencoded content from server to client. This allows to eliminate one RTT cycle for every video segment, which has a significant impact on the user's QoE. Evaluating the proposed approach, we show that compared with HTTP/1.1, an improvement of 65.42% can be achieved for the average video quality in high-RTT networks. Compared to an AVC-based solution, the freeze frequency and duration are reduced by 54.55% and 53.06% respectively, while the loss in video quality is limited to 4.51%. Since playout freezes should be avoided at the cost of a lower video quality, we conclude that the proposed approach beneficially impacts the user's QoE.

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“…MPEG-DASH has been proposed for CCN in [15] and been research very much in ICN in the last three years. On the other hand, SVS which provide the scalability through layering, as we have discussed in detail in Section 3.2, is envisioned to be very beneficial for CCN [12,24]. SVC encoder transcodes video in layers and store all the layers in one file.…”

Section: Related Workmentioning

confidence: 99%

“…This bandwidth unpredictability severely affects the video quality selection of AVC-based encoded videos. [24] has introduced the usage of SVC-based encoded videos in ICN/CCN to overcome the quality selection problem of AVC. The paper shows advantages of SVC in ICN over AVC both theoretically as well as through simulations.…”

Section: Related Workmentioning

confidence: 99%

Management of scalable video streaming in information centric networking

Ullah

Thar

Hong

2016

Multimed Tools Appl

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Ability of caching the contents is one of the most important feature of an Information Centric Networking (ICN) node. By managing the cache space intelligently we can improve network's performance and increase users' Quality of Experience (QoE). Moreover, scalable video streaming in ICN is envisioned to be very beneficial as well as a challenging issue. In this paper, we are proposing a mechanism for cache management and request forwarding policies for scalable video streaming in ICN. Our proposed cache decision policy ensures to cache the base layer of a scalable video near to the users, which is mandatory layer for decoding any SVC encoded video and is needed by all the users with any data-rate budget, and consequently cache the higher layers in the upper nodes in the CCN/ICN within a specific RTT range. Furthermore, our intelligent cache decision cover fairness by considering router's cache capacity (inside the RTT range) and at the same time giving more priority to the nodes that are nearer to the users. A limited cooperative request forwarding mechanism, which is the part of our proposal, plays a role to improve users' QoE by providing the popular requested contents quickly. We have intensively simulated our proposed cache management and request forwarding scheme. The simulation results show that our proposed solution outperforms the current cache management schemes and improve the cache utilization. Also our proposed scheme decrease the traffic flowing inside the network by eliminating the request flooding and providing the requested contents from the nearby location to the users. The proposed scheme provides video faster to the users, specially the mandatory base layer is provided very quickly to the users.

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Towards SVC-based Adaptive Streaming in information centric networks

Cited by 22 publications

References 9 publications

Clustering‐based quality selection heuristics for HTTP adaptive streaming over cache networks

Clustering‐based quality selection heuristics for HTTP adaptive streaming over cache networks

An HTTP/2 push-based approach for SVC adaptive streaming

Management of scalable video streaming in information centric networking

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