Es-Has

Farahani, Reza; Tashtarian, Farzad; Timmerer, Christian; Ghanbari, Mohammad; Hellwagner, Hermann

doi:10.1145/3458306.3460997

Cited by 18 publications

(1 citation statement)

References 20 publications

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“…In Cevallos Moreno et al, 16 an approach was proposed for defining the placement of video streaming VNFs such as cache, transcoder, compressor, and streamer by considering the capacities of VNFs containers. The studies were proposed to use a virtualized proxy servers or caches, which selects which content from which virtualized server for HAS systems in Farahani et al 17,18 …”

Section: Introductionmentioning

confidence: 99%

vDANE: Using virtualization for improving video quality with Server and Network Assisted DASH

2022

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Summary Network Function Virtualization (NFV) offers flexibility in traffic engineering and network resource management, by taking advantage of Software Defined Networking (SDN). By using these network technologies, it is possible to enhance the performance of video streaming applications by placing network functions in suitable locations and rerouting flows. Our study addresses the “virtual cache placement” problem in dynamic networks, where traffic patterns and attachment points of the clients are changing rapidly. The cache placement is done by determining how many virtual caches are necessary to be able to provide acceptable service to the clients, as well as where to place those caches to meet demand. To this end, we provide a heuristic solution by taking advantage of NFV‐SDN and having the assistance of Server and Network Assisted DASH (SAND). Experimental results show that the proposed algorithms can improve the video client rebuffering by 150%–270% and also can provide an 8%–12% increase in average bitrate received by the client, compared to a number of benchmark algorithms. The obtained results indicate that the co‐operation between the client and the operator of an SDN‐enabled network, by exchanging client and network information, allows network resources to be efficiently used, and as a consequence, the Quality of Experience (QoE) on the client's side is improved.

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Section: Introductionmentioning

confidence: 99%

vDANE: Using virtualization for improving video quality with Server and Network Assisted DASH

2022

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Content-aware QoE optimization in MEC-assisted Mobile video streaming

Rahman

Huh

2023

Multimed Tools Appl

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The traditional client-based HTTP adaptation strategies do not explicitly coordinate between the clients, servers, and cellular networks. A lack of coordination leads to suboptimal user experience. In addition to optimizing Quality of Experience (QoE), other challenges in adapting HTTP adaptive streaming (HAS) to the cellular environment are overcoming unfair allocation of the video rate and inefficient utilization of the bandwidth under the high-dynamics cellular links. Furthermore, the majority of the adaptive strategies ignore important video content characteristics and HAS client information, such as segment duration, buffer size, and video duration, in the video quality selection process. In this paper, we present a content-aware hybrid multi-access edge computing (MEC)-assisted quality adaptation algorithm by taking advantage of the capabilities of edge cloud computing. The proposed algorithm exploits video content characteristics, HAS client settings, and application-layer information to jointly adapt the bitrates of multiple clients. We design separate strategies to optimize the performance of short and long duration videos. We then demonstrate the efficiency of our algorithm against client-based solutions as well as MEC-assisted algorithms. The proposed algorithm guarantees high QoE, equitably selects video rates for clients, and efficiently utilizes the bandwidth for both short and long duration videos. The results from our extensive experiments reveal that the proposed long video adaptation algorithm outperforms state-of-the-art algorithms, with improvements in average video rate, QoE, fairness, and bandwidth utilization of 0.4%–12.3%, 8%–65%, 3.3%–5.7%, and 60%–130%, respectively. Furthermore, when high bandwidth is available to competing clients, the proposed short video adaptation algorithm improves QoE by 11.1% compared to the long video adaptation algorithm.

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An Orchestrator Architecture for Multi-tier Edge/Cloud Video Streaming Services

Gama,

Immich

et al. 2023

2023 IEEE International Conference on Edge Computing and Communications (EDGE)

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Es-Has

Cited by 18 publications

References 20 publications

vDANE: Using virtualization for improving video quality with Server and Network Assisted DASH

vDANE: Using virtualization for improving video quality with Server and Network Assisted DASH

Content-aware QoE optimization in MEC-assisted Mobile video streaming

An Orchestrator Architecture for Multi-tier Edge/Cloud Video Streaming Services

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