QCSS: A QoE-Aware Control Plane for Adaptive Streaming Service over Mobile Edge Computing Infrastructures
Abstract
Mobile Edge Computing (MEC) is designed to extend the edge of the cloud network to decrease latency and network congestion, which would significantly improve the quality of experience (QoE) of adaptive streaming service for mobile users. This paper proposes QCSS, a QoE-aware control plane for adaptive streaming service over MEC infrastructures. QCSS aims to assure high QoE delivery of online streaming service to mobile users. The design of QCSS features: 1) a timeslot system with a look-ahead window for calculating cost of edge node switch and video quality adaption (to balance network load and reduce latency); 2) conducting service adaption via a set of cooperative action components running on client devices, edge nodes, and center nodes (to ensure a smooth viewing experience); 3) constructing a flexible QoE model and extending the scope and meaning of user-perceived experience. The effectiveness of QCSS has been validated via three real datasets. The validation results show that the proposed QCSS can improve QoE performance and network load performance for adaptive streaming service over MEC Infrastructures.
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Dynamic adaptive streaming over HTTP --
Stockhammer, T. (2011) · doi:10.1145/1943552.1943572 · Cited by 1,236 · see citing works
A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP
Yin, X., Jindal, A., Sekar, V., & Sinopoli, B. (2015) · ACM Special Interest Group on Data Communication · doi:10.1145/2785956.2787486 · Cited by 1,030 · see citing works
A buffer-based approach to rate adaptation
Huang, T.-Y., Ramesh Johari, B., McKeown, N., Trunnell, M., & Watson, M. (2014) · ACM SIGCOMM Conference (SIGCOMM) · doi:10.1145/2619239.2626296 · Cited by 1,007 · see citing works
Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with FESTIVE
Jiang, J., Sekar, V., & Zhang, H. (2012) · ACM International Conference on emerging Networking EXperiments and Technologies (CoNEXT) · doi:10.1145/2413176.2413189 · Cited by 694 · see citing works
BOLA: Near-optimal bitrate adaptation for online videos
Spiteri, K., Urgaonkar, R., & Sitaraman, R. K. (2016) · doi:10.1109/infocom.2016.7524428 · Cited by 507 · see citing works
Rate adaptation for adaptive HTTP streaming
Liu, C., Bouazizi, I., & Gabbouj, M. (2011) · doi:10.1145/1943552.1943575 · Cited by 466 · see citing works
CS2P: Improving Video Bitrate Selection and Adaptation with Data-Driven Throughput Prediction
Sun, Y., Yin, X., Jiang, J., Sekar, V., Lin, F., Wang, N., Liu, T., & Sinopoli, B. (2016) · Proceedings of the 2016 ACM SIGCOMM Conference · doi:10.1145/2934872.2934898 · Cited by 407 · see citing works
A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP
Yin, X., Jindal, A., Sekar, V., et al. (2015) · ACM SIGCOMM Computer Communication Review · doi:10.1145/2829988.2787486 · Cited by 378 · see citing works
A Survey of Rate Adaptation Techniques for Dynamic Adaptive Streaming Over HTTP
Kua, J., Armitage, G. J., & Branch, P. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2685630 · Cited by 323 · see citing works
Feedback control for adaptive live video streaming
Cicco, L. D., Mascolo, S., & Palmisano, V. (2011) · doi:10.1145/1943552.1943573 · Cited by 228 · see citing works
ELASTIC: A Client-Side Controller for Dynamic Adaptive Streaming over HTTP (DASH)
Cicco, L. D., Caldaralo, V., Palmisano, V., et al. (2013) · International Packet Video Workshop (PV) · doi:10.1109/pv.2013.6691442 · Cited by 226 · see citing works
A case for a coordinated internet video control plane
Liu, X., Dobrian, F., Milner, H., Jiang, J., Sekar, V., Stoica, I. G., & Zhang, H. (2012) · ACM SIGCOMM Conference (SIGCOMM) · doi:10.1145/2342356.2342431 · Cited by 224 · see citing works
Downton abbey without the hiccups
Huang, T.-Y., Johari, R., & McKeown, N. (2013) · doi:10.1145/2491172.2491179 · Cited by 112 · see citing works
Toward a Principled Framework to Design Dynamic Adaptive Streaming Algorithms over HTTP
Yin, X., Sekar, V., & Sinopoli, B. (2014) · ACM Workshop on Hot Topics in Networks (HotNets) · doi:10.1145/2670518.2673877 · Cited by 86 · see citing works
Bęben, A., Wiśniewski, P., Batalla, J. M., & Krawiec, P. (2016) · ACM Multimedia Systems Conference (MMSys) · doi:10.1145/2910017.2910596 · Cited by 55 · see citing works
A case for a coordinated internet video control plane
Liu, X., Dobrian, F., Milner, H., et al. (2012) · ACM SIGCOMM Computer Communication Review · doi:10.1145/2377677.2377752 · Cited by 46 · see citing works
Adaptive video pacing method based on the prediction of stochastic TCP throughput
Satoda, K., Yoshida, H., Ito, H., et al. (2012) · Globecom · doi:10.1109/glocom.2012.6503400 · Cited by 19 · see citing works
QoECenter: A Visual Platform for QoE Evaluation of Streaming Video Services
Zhang, L., Wang, S., Yang, F., & Chang, R. (2017) · IEEE International Conference on Web Services (ICWS) · doi:10.1109/icws.2017.35 · Cited by 9 · see citing works
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QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
Barakabitze, A. A., Barman, N., Ahmad, A., Zadtootaghaj, S., Sun, L., Martini, M. G., & Atzori, L. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2958784 · Cited by 239 · see citing works
- Authors
- Zhang, L., Wang, S., & Chang, R. N.
- Affiliations
- Beijing University of Posts and Telecommunications (CN)
- IBM (United States) (US)
- Venue
- 2018 IEEE International Conference on Web Services (ICWS)
- Publisher
- IEEE
- Published
- 2018-07
- Pages
- 139-146
- OpenAlex
- W2889901890
- Cited by
- 14
- References
- 18
- Citations by year
- 2024: 3 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 3 · 2018: 1
- FWCI
- 1.65
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Web Services (ICWS) (publishedVersion)
- Funders
- National Science Foundation
- Ministerio de Economía y Competitividad
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Computer Science › Computer Networks and Communications › Caching and Content Delivery
- Keywords
- mobile edge computing, adaptive video streaming, quality of experience, control plane, video quality adaptation, network load balancing, latency reduction, QoE model
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