Green Video Streaming: Challenges and Opportunities

Green Video Streaming: Challenges and Opportunities

SIGMM Records Column

Samira Afzal (Alpen-Adria-Universität (AAU) Klagenfurt, Austria), Radu Prodan (Alpen-Adria-Universität (AAU) Klagenfurt, Austria), Christian Timmerer (Alpen-Adria-Universität (AAU) Klagenfurt and Bitmovin Inc., Austria)

Introduction:

Regarding the Intergovernmental Panel on Climate Change (IPCC) report in 2021 and Sustainable Development Goal (SDG) 13 “climate action”, urgent action is needed against climate change and global greenhouse gas (GHG) emissions in the next few years [1]. This urgency also applies to the energy consumption of digital technologies. Internet data traffic is responsible for more than half of digital technology’s global impact, which is 55% of energy consumption annually. The Shift Project forecast [2] shows an increase of 25% in data traffic associated with 9% more energy consumption per year, reaching 8% of all GHG emissions in 2025.

Video flows represented 80% of global data flows in 2018, and this video data volume is increasing by 80% annually [2].  This exponential increase in the use of streaming video is due to (i) improvements in Internet connections and service offerings [3], (ii) the rapid development of video entertainment (e.g., video games and cloud gaming services), (iii) the deployment of Ultra High-Definition (UHD, 4K, 8K), Virtual Reality (VR), and Augmented Reality (AR), and (iv) an increasing number of video surveillance and IoT applications [4]. Interestingly, video processing and streaming generate 306 million tons of CO2, which is 20% of digital technology’s total GHG emissions and nearly 1% of worldwide GHG emissions [2].

While research has shown that the carbon footprint of video streaming has been decreasing in recent years [5], there is still a high need to invest in research and development of efficient next-generation computing and communication technologies for video processing technologies. This carbon footprint reduction is due to technology efficiency trends in cloud computing (e.g., renewable power), emerging modern mobile networks (e.g., growth in Internet speed), and end-user devices (e.g., users prefer less energy-intensive mobile and tablet devices over larger PCs and laptops). However, since the demand for video streaming is growing dramatically, it raises the risk of increased energy consumption.

Investigating energy efficiency during video streaming is essential to developing sustainable video technologies. The processes from video encoding to decoding and displaying the video on the end user’s screen require electricity, which results in CO2 emissions. Consequently, the key question becomes: “How can we improve energy efficiency for video streaming systems while maintaining an acceptable Quality of Experience (QoE)?”.

 

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Perceptually-aware Live VBR Encoding Scheme for Adaptive AVC Streaming

2023 NAB Broadcast Engineering and Information Technology (BEIT) Conference

April 15-19, 2023 | Las Vegas, US

Conference Website

Vignesh V Menon (Alpen-Adria-Universität Klagenfurt),  Prajit T Rajendran (Universite Paris-Saclay), Christian Feldmann (Bitmovin, Klagenfurt), Martin Smole (Bitmovin, Klagenfurt), Klaus Schoeffmann (Alpen-Adria-Universität Klagenfurt), Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK)and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).

Abstract:

Currently, a fixed set of bitrate-resolution pairs termed bitrate ladder is used in live streaming applications. Similarly, two-pass variable bitrate (VBR) encoding schemes are not used in live streaming applications to avoid the additional latency added by the first-pass. Bitrate ladder optimization is necessary to (i) decrease storage or delivery costs or/and (ii) increase Quality of Experience (QoE). Using two-pass VBR encoding improves compression efficiency, owing to better encoding decisions in the second-pass encoding using the first-pass analysis. In this light, this paper introduces a perceptually-aware constrained Variable Bitrate (cVBR) encoding Scheme (Live VBR) for HTTP adaptive streaming applications, which includes a joint optimization of the perceptual redundancy between the representations of the bitrate ladder, maximizing the perceptual quality (in terms of VMAF) and optimized constant rate factor (CRF). Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features for every video segment, namely, brightness, spatial texture information, and temporal activity, are extracted to predict perceptually-aware bitrate ladder for encoding. Experimental results show that, on average, Live VBR yields bitrate savings of 18.80% and 32.59% to maintain the same PSNR and VMAF, respectively, compared to the reference HTTP Live Streaming (HLS) bitrate ladder Constant Bitrate (CBR) encoding using x264 AVC encoder without any noticeable additional latency in streaming, accompanied by a 68.96% cumulative decrease in storage space for various representations, and a 28.25% cumulative decrease in energy consumption, considering a perceptual difference of 6 VMAF points.

The encoding pipeline using Live VBR envisioned in this paper.

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SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

IEEE International Conference on Communications (ICC)

28 May – 01 June 2023– Rome, Italy

Conference Website
[PDF][Slides]

Reza Farahani (Alpen-Adria-Universität Klagenfurt),  Abdelhak Bentaleb (Concordia University, Canada), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Mohammad Shojafar (University of Surrey, UK), Radu Prodan (Alpen-Adria-Universität Klagenfurt), and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt).

Abstract: 5G and 6G networks are expected to support various novel emerging adaptive video streaming services (e.g., live, VoD, immersive media, and online gaming) with versatile Quality of Experience (QoE) requirements such as high bitrate, low latency, and sufficient reliability. It is widely agreed that these requirements can be satisfied by adopting emerging networking paradigms like Software-Defined Networking (SDN), Network Function Virtualization (NFV), and edge computing. Previous studies have leveraged these paradigms to present network-assisted video streaming frameworks, but mostly in isolation without devising chains of Virtualized Network Functions (VNFs) that consider the QoE requirements of various types of Multimedia Services (MS).

To bridge the aforementioned gaps, we first introduce a set of multimedia VNFs at the edge of an SDN-enabled network, form diverse Service Function Chains (SFCs) based on the QoE requirements of different MS services. We then propose SARENA, an SFC-enabled ArchitectuRe for adaptive VidEo StreamiNg Applications. Next, we formulate the problem as a central scheduling optimization model executed at the SDN controller. We also present a lightweight heuristic solution consisting of two phases that run on the SDN controller and edge servers to alleviate the time complexity of the optimization model in
large-scale scenarios. Finally, we design a large-scale cloud-based testbed, including 250 HTTP Adaptive Streaming (HAS) players requesting two popular MS applications (i.e., live and VoD), conduct various experiments, and compare its effectiveness with baseline systems. Experimental results illustrate that SARENA outperforms baseline schemes in terms of users’ QoE by at least 39.6%, latency by 29.3%, and network utilization by 30% in both MS services.

Index TermsHAS; DASH; NFV; SFC; SDN, Edge Computing.

 

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A holistic survey of multipath wireless video streaming

A holistic survey of multipath wireless video streaming

Journal Website: Journal of Network and Computer Applications

[PDF]

Samira Afzal (Alpen-Adria-Universität Klagenfurt), Vanessa Testoni (unico IDtech), Christian Esteve Rothenberg (University of Campinas), Prakash Kolan (Samsung Research America), and Imed Bouazizi (Qualcomm)

Abstract:

Demand for wireless video streaming services increases with users expecting to access high-quality video streaming experiences. Ensuring Quality of Experience (QoE) is quite challenging due to varying bandwidth and time constraints. Since most of today’s mobile devices are equipped with multiple network interfaces, one promising approach is to benefit from multipath communications. Multipathing leads to higher aggregate bandwidth and distributing video traffic over multiple network paths improves stability, seamless connectivity, and QoE. However, most of current transport protocols do not match the requirements of video streaming applications or are not designed to address relevant issues, such as networks heterogeneity, head-of-line blocking, and delay constraints. In this comprehensive survey, we first review video streaming standards
and technology developments. We then discuss the benefits and challenges of multipath video transmission over wireless. We provide a holistic literature review of multipath wireless video streaming, shedding light on the different alternatives from an end-to-end layered stack perspective, reviewing key multipath wireless scheduling functions, unveiling trade-offs of each approach, and presenting a suitable taxonomy to classify the
state-of-the-art. Finally, we discuss open issues and avenues for future work.

 

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Reza Farahani to give a talk at 5G/6G Innovation Center, University of Surrey, UK

Collaborative Edge-Assisted Systems for HTTP Adaptive Video Streaming

5G/6G Innovation Center,  University of Surrey, UK

6th January 2023 | Guildford, UK

Abstract: The proliferation of novel video streaming technologies, advancement of networking paradigms, and steadily increasing numbers of users who prefer to watch video content over the Internet rather than using classical TV have made video the predominant traffic on the Internet. However, designing cost-effective, scalable, and flexible architectures that support low-latency and high-quality video streaming is still a challenge for both over-the-top (OTT) and ISP companies. In this talk, we first introduce the principles of video streaming and the existing challenges. We then review several 5G/6G networking paradigms and explain how we can leverage networking technologies to form collaborative network-assisted video streaming systems for improving users’ quality of experience (QoE) and network utilization.

Reza Farahani is a last-year Ph.D. candidate at the University of Klagenfurt, Austria, and a Ph.D. visitor at the University of Surrey, Uk. He received his B.Sc. in 2014 and M.Sc. in 2019 from the university of Isfahan, IRAN, and the university of Tehran, IRAN, respectively. Currently, he is working on the ATHENA project in cooperation with its industry partner Bitmovin. His research is focused on designing modern network-assisted video streaming solutions (via SDN, NFV, MEC, SFC, and P2P paradigms), multimedia Communication, computing continuum challenges, and parallel and distributed systems. He also worked in different roles in the computer networks field, e.g., network administrator, ISP customer support engineer, Cisco network engineer, network protocol designer, network programmer, and Cisco instructor (R&S, SP).

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LALISA: Adaptive Bitrate Ladder Optimization in HTTP-based Adaptive Live Streaming

LALISA: Adaptive Bitrate Ladder Optimization in HTTP-based Adaptive Live Streaming

IEEE/IFIP Network Operations and Management Symposium (NOMS)

8-12 May 2023- Miami, FL – USA

[PDF][PPT][Video]

Farzad Tashtarian (Alpen-Adria-Universität Klagenfurt, Austria), Abdelhak Bentaleb (Concordia University, Canada), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria), Babak Taraghi (Alpen-Adria-Universität Klagenfurt, Austria), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt, Austria), Roger Zimmermann (National University of Singapore, Singapore)

Video content in Live HTTP Adaptive Streaming (HAS) is typically encoded using a pre-defined, fixed set of bitrate-resolution pairs (termed Bitrate Ladder), allowing playback devices to adapt to changing network conditions using an adaptive bitrate (ABR) algorithm. However, using a fixed one-size-fits-all solution when faced with various content complexities, heterogeneous network conditions, viewer device resolutions and locations, does not result in an overall maximal viewer quality of experience (QoE). Here, we consider these factors and design LALISA, an efficient framework for dynamic bitrate ladder optimization in live HAS. LALISA dynamically changes a live video session’s bitrate ladder, allowing improvements in viewer QoE and savings in encoding, storage, and bandwidth costs. LALISA is independent of ABR algorithms and codecs, and is deployed along the path between viewers and the origin server. In particular, it leverages the latest developments in video analytics to collect statistics from video players, content delivery networks and video encoders, to perform bitrate adder tuning. We evaluate the performance of LALISA against existing solutions in various video streaming scenarios using a trace-driven testbed. Evaluation results demonstrate significant improvements in encoding computation (24.4%) and bandwidth (18.2%) costs with an acceptable QoE.

 

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CD-LwTE: Cost- and Delay-aware Light-weight Transcoding at the Edge

CD-LwTE: Cost- and Delay-aware Light-weight Transcoding at the Edge

IEEE Transactions on Network and Service Management (TNSM)

[PDF]

Alireza Erfanian (Alpen-Adria-Universität Klagenfurt, Austria), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt, Austria), Farzad Tashtarian (Alpen-Adria-Universität Klagenfurt, Austria), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria), and Hermann Hellwagner.

Abstract—The edge computing paradigm brings cloud capabilities close to the clients. Leveraging the edge’s capabilities can improve video streaming services by employing the storage capacity and processing power at the edge for caching and transcoding tasks, respectively, resulting in video streaming services with higher quality and lower latency. In this paper, we propose CD-LwTE, a Cost- and Delay-aware Light-weight Transcoding approach at the Edge, in the context of HTTP Adaptive Streaming (HAS). The encoding of a video segment requires computationally intensive search processes. The main idea of CD-LwTE is to store the optimal search results as metadata for each bitrate of video segments and reuse it at the edge servers to reduce the required time and computational resources for transcoding. Aiming at minimizing the cost and delay of Video-on-Demand (VoD) services, we formulate the problem of selecting an optimal policy for serving segment requests at the edge server, including (i) storing at the edge server, (ii) transcoding from a higher bitrate at the edge server, and (iii) fetching from the origin or a CDN server, as a Binary Linear Programming (BLP) model. As a result, CD-LwTE stores the popular video segments at the edge and serves the unpopular ones by transcoding using metadata or fetching from the origin/CDN server. In this way, in addition to the significant reduction in bandwidth and storage costs, the transcoding time of a requested segment is remarkably decreased by utilizing its corresponding metadata. Moreover, we prove the proposed BLP model is an NP-hard problem and propose two heuristic algorithms to mitigate the time complexity of CD-LwTE. We investigate the performance of CD-LwTE in comprehensive scenarios with various video contents, encoding software, encoding settings, and available resources at the edge. The experimental results show that our approach (i) reduces the transcoding time by up to 97%, (ii) decreases the streaming cost, including storage, computation, and bandwidth costs, by up to 75%, and (iii) reduces delay by up to 48% compared to state-of-the-art approaches.

 

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