The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
SDNDASH: Improving QoE of HTTP Adaptive Streaming Using Software Defined Networking
Abstract
HTTP adaptive streaming (HAS) is being adopted with increasing frequency and becoming the de-facto standard for video streaming. However, the client-driven, on-off adaptation behavior of HAS results in uneven bandwidth competition and this is exacerbated when a large number of clients share the same bottleneck network link and compete for the available bandwidth. With HAS each client independently strives to maximize its individual share of the available bandwidth, which leads to bandwidth competition and a decrease in end-user quality of experience (QoE). The competition causes scalability issues, which are quality instability, unfair bandwidth sharing and network resource underutilization. We propose a new software defined networking (SDN) based dynamic resource allocation and management architecture for HAS systems, which aims to alleviate these scalability issues and improve the per-client QoE. Our architecture manages and allocates the network resources dynamically for each client based on its expected QoE. Experimental results show that the proposed architecture significantly enhances scalability by improving per-client QoE by at least 30% and supporting up to 80% more clients with the same QoE compared to the conventional schemes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“With SAND, bandwidth reservation and bitrate guidance strategies have attracted much attention in the multimedia streaming community [7], [107] [198], [196].”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [198]
In the citing paper
“Some of the approaches, for example in [7,198], employ an optimization function that interacts with the controller to dynamically optimize QoE fairness of multiple competing clients by setting the bitrate for each streaming video in the network.”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [198]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
McKeown (2008) · doi:10.1145/1355734.1355746 · Cited by 8,513
Lee, J. H., Kaisare, N. S., & García, C. E. (2007) · Springer eBooks · doi:10.1002/9781394333325.fmatter · Cited by 3,766
Dynamic adaptive streaming over HTTP --
Stockhammer, T. (2011) · doi:10.1145/1943552.1943572 · Cited by 1,236
Huang, B., Qi, Y., & Murshed, A. M. (2012) · doi:10.1002/9781118501054.ch6 · Cited by 1,047
A Survey on Quality of Experience of HTTP Adaptive Streaming
Seufert, M., Egger, S., Slanina, M., Zinner, T., Hoßfeld, T., & Tran-Gia, P. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2360940 · Cited by 844
A generic quantitative relationship between quality of experience and quality of service
Fiedler, M., Hossfeld, T., & Tran-Gia, P. (2010) · IEEE Network · doi:10.1109/mnet.2010.5430142 · Cited by 837
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
What happens when HTTP adaptive streaming players compete for bandwidth?
Akhshabi, S., Anantakrishnan, L., Begen, A. C., & Dovrolis, C. (2012) · doi:10.1145/2229087.2229092 · Cited by 343
Self-citationMok, R. K. P., Luo, X., Chan, E. W. W., & Chang, R. K. C. (2012) · ACM Multimedia Systems Conference (MMSys) · doi:10.1145/2155555.2155558 · Cited by 331
Towards network-wide QoE fairness using openflow-assisted adaptive video streaming
Georgopoulos, P., Elkhatib, Y., Broadbent, M., Mu, M., & Race, N. (2013) · Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking · doi:10.1145/2491172.2491181 · Cited by 242
Flagged first, then by citations
Research works printed but not linked: 2
- Index C. V. N., 2014, The Zettabyte Era--Trends and Analysis. Cisco white paper
- Li Z., 2014, Probe and Adapt: Rate Adaptation for HTTP Video Streaming at Scale. Selected Areas in Communications, IEEE Journal on, 32, 719
Cited by
Sorted by citations
A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP
Bentaleb, A., Taani, B., Begen, A. C., Timmerer, C., & Zimmermann, R. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2862938 · Cited by 498
Self-citationQoE 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
A Quality-of-Experience Database for Adaptive Video Streaming
Duanmu, Z., Rehman, A., & Wang, Z. (2018) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2018.2822870 · Cited by 146
Comyco: Quality-Aware Adaptive Video Streaming via Imitation Learning
Huang, T., Zhou, C., Zhang, R.-X., Wu, C., Yao, X., & Sun, L. (2019) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3343031.3351014 · Cited by 124
A Survey of Emerging Concepts and Challenges for QoE Management of Multimedia Services
Skorin-Kapov, L., Varela, M., Hoßfeld, T., & Chen, K.-T. (2018) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3176648 · Cited by 116
Edge Computing Assisted Adaptive Mobile Video Streaming
Mehrabi, A., Siekkinen, M., & Ylä-Jääski, A. (2018) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2018.2850026 · Cited by 111
SDNHAS: An SDN-Enabled Architecture to Optimize QoE in HTTP Adaptive Streaming
Bentaleb, A., Begen, A. C., Zimmermann, R., & Harous, S. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2733344 · Cited by 99
Self-citationImproving Quality of Experience by Adaptive Video Streaming with Super-Resolution
Zhang, Y., Zhang, Y., Wu, Y. J., Tao, Y., Bian, K., Zhou, P., Song, L., & Tuo, H. (2020) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom41043.2020.9155384 · Cited by 96
Nasralla, M. M., Khattak, S. B. A., Rehman, I. U., & Iqbal, M. (2023) · Sensors · doi:10.3390/s23135882 · Cited by 92
Towards Perceptually Optimized End-to-end Adaptive Video StreamingPreprint
Bampis, C. G., Li, Z., Katsavounidis, I. X., Huang, T.-Y., Ekanadham, C., & Bovik, A. C. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.03898 · Cited by 69
Adaptive Bitrate with User-level QoE Preference for Video Streaming
Zuo, X., Yang, J., Wang, M., & Cui, Y. (2022) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom48880.2022.9796953 · Cited by 71
Quality-Aware Neural Adaptive Video Streaming With Lifelong Imitation Learning
Huang, T., Zhou, C., Yao, X., Zhang, R.-X., Wu, C., Yu, B., & Sun, L. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000363 · Cited by 64
Mehrabi, A., Siekkinen, M., Kämäräinen, T., & Ylä-Jääski, A. (2021) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3429441 · Cited by 58
QoE-SDN APP: A Rate-guided QoE-aware SDN-APP for HTTP Adaptive Video Streaming
Liotou, E., Samdanis, K., Pateromichelakis, E., Passas, N. I., & Merakos, L. F. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2815421 · Cited by 52
Duanmu, Z., Ma, K., & Wang, Z. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2855403 · Cited by 54
Towards Perceptually Optimized Adaptive Video Streaming-A Realistic Quality of Experience Database
Bampis, C. G., Li, Z., Katsavounidis, I. X., Huang, T.-Y., Ekanadham, C., & Bovik, A. C. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3073294 · Cited by 49
Optimizing Quality of Experience for Adaptive Bitrate Streaming via Viewer Interest Inference
Gao, G., Zhang, H., Hu, H., Wen, Y., Cai, J., Luo, C., & Zeng, W. (2018) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2018.2838330 · Cited by 44
Bentaleb, A., Begen, A. C., Harous, S., & Zimmermann, R. (2018) · ACM Multimedia Systems Conference (MMSys) · doi:10.1145/3204949.3204961 · Cited by 44
Self-citationNetwork Assisted Content Distribution for Adaptive Bitrate Video Streaming
Bhat, D., Rizk, A., Zink, M., & Steinmetz, R. (2017) · ACM Multimedia Systems Conference (MMSys) · doi:10.1145/3083187.3083196 · Cited by 43
Quality of Experience-Centric Management of Adaptive Video Streaming Services: Status and Challenges
Petrangeli, S., Hooft, J. V. D., Wauters, T., & Turck, F. D. (2018) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3165266 · Cited by 38
Tile Rate Allocation for 360-Degree Tiled Adaptive Video Streaming
Yadav, P. K., & Ooi, W. T. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413550 · Cited by 38
Data-Driven Bandwidth Prediction Models and Automated Model Selection for Low Latency
Bentaleb, A., Begen, A. C., Harous, S., & Zimmermann, R. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3013387 · Cited by 36
Self-citationBoB: Bandwidth Prediction for Real-Time Communications Using Heuristic and Reinforcement Learning
Bentaleb, A., Akcay, M. N., Lim, M. L., Begen, A. C., & Zimmermann, R. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3216456 · Cited by 39
Self-citationCompete or Collaborate: Architectures for Collaborative DASH Video Over Future Networks
Bagci, K. T., Sahin, K. E., & Tekalp, A. M. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2736638 · Cited by 34
Q-FDBA: improving QoE fairness for video streaming
Jiang, J., Hu, L., Hao, P., Sun, R., Hu, J., & Li, H. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-017-4917-1 · Cited by 31
Optimizing Adaptive Video Streaming with Human Feedback
Huang, T., Zhang, R.-X., Wu, C., & Sun, L. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611771 · Cited by 38
ARARAT: A Collaborative Edge-Assisted Framework for HTTP Adaptive Video Streaming
Farahani, R., Shojafar, M., Timmerer, C., Tashtarian, F., Ghanbari, M., & Hellwagner, H. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3210595 · Cited by 29
$\mathsf{HxL3}$: Optimized Delivery Architecture for HTTP Low-Latency Live Streaming
Tashtarian, F., Bentaleb, A., Erfanian, A., Hellwagner, H., Timmerer, C., & Zimmermann, R. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3148587 · Cited by 28
Self-citationQoE-Aware Bandwidth Broker for HTTP Adaptive Streaming Flows in an SDN-Enabled HFC Network
Bentaleb, A., Begen, A. C., & Zimmermann, R. (2018) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2018.2816789 · Cited by 27
Self-citationBhat, D., Rizk, A., Zink, M., & Steinmetz, R. (2018) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3183516 · Cited by 25
Fault tolerance in SDN data plane considering network and application based metrics
Yamansavascilar, B., Baktır, A. C., Özgövde, A., & Ersoy, C. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102780 · Cited by 25
Common media client data (CMCD)
Bentaleb, A., Lim, M. L., Akcay, M. N., Begen, A. C., & Zimmermann, R. (2021) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3458306.3461444 · Cited by 25
Self-citationAssessing the Quality-of-Experience of Adaptive Bitrate Video StreamingPreprint
Duanmu, Z., Liu, W., Li, Z., Chen, D., Wang, Z., Wang, Y., & Gao, W. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.08804 · Cited by 25
Bentaleb, A., Yadav, P. K., Ooi, W. T., & Zimmermann, R. (2020) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3371040 · Cited by 24
Self-citationImproving Video Quality in Crowded Networks Using a DANE
Kleinrouweler, J. W., Meixner, B., & Cesar, P. S. (2017) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3083165.3083167 · Cited by 22
Taming the Wild: A Scalable Anycast-Based CDN Architecture (T-SAC)
Fu, Q., Rutter, B., Li, H., Zhang, P., Hu, C., Pan, T., Huang, Z., & Hou, Y. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2871323 · Cited by 22
An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial
Peroni, L., & Gorinsky, S. (2025) · ACM Computing Surveys · doi:10.1145/3742472 · Cited by 21
Farahani, R., Tashtarian, F., Erfanian, A., Timmerer, C., Ghanbari, M., & Hellwagner, H. (2021) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3458306.3460997 · Cited by 21
S2VC: An SDN-based framework for maximizing QoE in SVC-based HTTP adaptive streaming
Tashtarian, F., Erfanian, A., & Varasteh, A. (2018) · Computer Networks · doi:10.1016/j.comnet.2018.09.007 · Cited by 20
A Real-Time Blind Quality-of-Experience Assessment Metric for HTTP Adaptive Streaming
Li, C., Lim, M. L., Bentaleb, A., & Zimmermann, R. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00286 · Cited by 21
Self-citationЛемешко, О. В., Yevdokymenko, M., & Alsaleem, N. Y. A. (2018) · Eastern-European Journal of Enterprise Technologies · doi:10.15587/1729-4061.2018.141989 · Cited by 19
CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming
Alt, B., Ballard, T., Steinmetz, R., Koeppl, H., & Rizk, A. (2019) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2019.8737418 · Cited by 20
A UAV-Centric Improved Soft Actor-Critic Algorithm for QoE-Focused Aerial Video Streaming
Yaqoob, A., Yuan, Z., & Muntean, G. (2024) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2024.3396349 · Cited by 19
QoE for Mobile Clients with Segment-aware Rate Adaptation Algorithm (SARA) for DASH Video Streaming
Yarnagula, H. K., Juluri, P., Mehr, S. K., Tamarapalli, V., & Medhi, D. (2019) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3311749 · Cited by 19
Edge Computing Assisted Adaptive Streaming Scheme for Mobile Networks
Kim, M., & Chung, K. (2020) · IEEE Access · doi:10.1109/access.2020.3047373 · Cited by 19
Quality of Experience-based Routing of Video Traffic for Overlay and ISP Networks
Calvigioni, G., Aparicio-Pardo, R., Sassatelli, L., Leguay, J., Medagliani, P., & Paris, S. (2018) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2018.8485954 · Cited by 18
Bentaleb, A., Begen, A. C., & Zimmermann, R. (2018) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3219752 · Cited by 18
Self-citationLearning-Based Joint QoE Optimization for Adaptive Video Streaming Based on Smart Edge
Ma, X., Li, Q., Jiang, Y., Muntean, G., & Zou, L. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3145619 · Cited by 17
Bitrate Adaptation and Guidance With Meta Reinforcement Learning
Bentaleb, A., Lim, M. L., Akcay, M. N., Begen, A. C., & Zimmermann, R. (2024) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2024.3376560 · Cited by 17
Self-citationJoint optimization of QoE and fairness through network assisted adaptive mobile video streaming
Mehrabi, A., Siekkinen, M., & Ylä-Jääski, A. (2017) · IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) · doi:10.1109/wimob.2017.8115778 · Cited by 17
Understanding quality of experience of heuristic-based HTTP adaptive bitrate algorithms
Taraghi, B., Bentaleb, A., Timmerer, C., Zimmermann, R., & Hellwagner, H. (2021) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3458306.3458875 · Cited by 17
Self-citationA Bayesian Quality-of-Experience Model for Adaptive Streaming Videos
Duanmu, Z., Liu, W., Chen, D., Li, Z., Wang, Z., Wang, Y., & Gao, W. (2022) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3491432 · Cited by 16
Alsader, M., Barakabitze, A. A., & Mkwawa, I.-H. M. (2025) · IEEE Access · doi:10.1109/access.2025.3597058 · Cited by 21
Meta Reinforcement Learning for Rate Adaptation
Bentaleb, A., Lim, M. L., Akcay, M. N., Begen, A. C., & Zimmermann, R. (2023) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom53939.2023.10228951 · Cited by 15
Self-citationBandwidth Prediction Schemes for Defining Bitrate Levels in SDN-enabled Adaptive Streaming
Al-Issa, A. E., Bentaleb, A., Barakabitze, A. A., Zinner, T., & Ghita, B. (2019) · International Conference on Network and Service Management (CNSM) · doi:10.23919/cnsm46954.2019.9012713 · Cited by 14
Self-citationSAND/3: SDN-Assisted Novel QoE Control Method for Dynamic Adaptive Streaming over HTTP/3
Guillen, L., Izumi, S., Abe, T., & Suganuma, T. (2019) · Electronics · doi:10.3390/electronics8080864 · Cited by 14
SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming
Kalan, R. S., & Sayit, M. F. (2021) · IEEE Access · doi:10.1109/access.2021.3114299 · Cited by 13
HTTP Adaptive Streaming: A Review on Current Advances and Future Challenges
Timmerer, C., Amirpour, H., Tashtarian, F., Afzal, S., Rizk, A., Zink, M., & Hellwagner, H. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3736306 · Cited by 13
Akpınar, K., & Hua, K. A. (2020) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3379983 · Cited by 13
Road to Salvation: Streaming Clients and Content Delivery Networks Working Together
Begen, A. C., Bentaleb, A., Silhavy, D., Pham, S., Zimmermann, R., & Law, W. (2021) · IEEE Communications Magazine · doi:10.1109/mcom.121.2100137 · Cited by 13
Self-citationSlicing aware QoS/QoE in software defined smart home network
Chaabnia, S., & Meddeb, A. (2018) · IEEE/IFIP Network Operations and Management Symposium (NOMS) · doi:10.1109/noms.2018.8406195 · Cited by 13
QoE Management for Future Networks
Schatz, R., Schwarzmann, S., Zinner, T., Dobrijević, O., Liotou, E., Počta, P., Baraković, S., Husić, J. B., & Skorin‐Kapov, L. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-90415-3_3 · Cited by 13
A Knowledge-Driven Quality-of-Experience Model for Adaptive Streaming VideosPreprint
Duanmu, Z., Liu, W., Chen, D., Li, Z., Wang, Z., Wang, Y., & Gao, W. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.07944 · Cited by 13
Seufert, M., Wehner, N., & Casas, P. (2019) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2019.2910380 · Cited by 15
Optimal QoE-Fair Resource Allocation in Multipath Video Delivery Network
Manfredi, G., Cicco, L. D., & Mascolo, S. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3162750 · Cited by 11
QoE-Driven Cross-Layer Bitrate Allocation Approach for MEC-Supported Adaptive Video Streaming
Yeznabad, Y. F., Helfert, M., & Muntean, G. (2024) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2024.3453992 · Cited by 11
Implementation of SAND Architecture Using SDN
Kalan, R. S., Sayit, M. F., & Begen, A. C. (2018) · IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) · doi:10.1109/nfv-sdn.2018.8725632 · Cited by 11
Self-citationA 360° Video Adaptive Streaming Scheme Based on Multiple Video Qualities
Zhang, J., Zhong, Y., Han, Y., Li, D., Yu, C., & Mo, J. (2020) · IEEE/ACM International Conference on Utility and Cloud Computing (UCC) · doi:10.1109/ucc48980.2020.00063 · Cited by 11
Multimedia Delivery Techniques over Software-Defined Networks: A Survey
Sanaei, M., & Mostafavi, S. (2019) · International Conference on Web Research (ICWR) · doi:10.1109/icwr.2019.8765278 · Cited by 11
D2D-Enabled Collaborative Edge Caching and Processing with Adaptive Mobile Video Streaming
Mehrabi, A., Siekkinen, M., Illahi, G. K., & Ylä-Jääski, A. (2019) · IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) · doi:10.1109/wowmom.2019.8792981 · Cited by 11
Jia, Z., Min, X., Sun, W., & Zhai, G. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3418941 · Cited by 10
A Distributed Approach for Bitrate Selection in HTTP Adaptive Streaming
Bentaleb, A., Begen, A. C., Harous, S., & Zimmermann, R. (2018) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3240508.3240589 · Cited by 10
Self-citationLearning-Based Online QoE Optimization in Multi-Agent Video Streaming
Wang, Y., Agarwal, M., Lan, T., & Aggarwal, V. (2022) · Algorithms · doi:10.3390/a15070227 · Cited by 10
View-Adaptive Streaming of Point Cloud Scenes through combined Decomposition and Video-based Coding
Rudolph, M., & Rizk, A. (2022) · doi:10.1145/3552457.3555732 · Cited by 10
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
Farahani, R., Bentaleb, A., Timmerer, C., Shojafar, M., Prodan, R., & Hellwagner, H. (2023) · International Conference on Communications · doi:10.1109/icc45041.2023.10279262 · Cited by 10
Self-citationAssisting Delay and Bandwidth Sensitive Applications in a Self-Driving Network
Madanapalli, S. C., Gharakheili, H. H., & Sivaraman, V. (2019) · ACM SIGCOMM Workshop on Network Meets AI & ML (NetAI) · doi:10.1145/3341216.3342215 · Cited by 10
Mustafa, I. B., Nadeem, T., & Halepovic, E. (2018) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3240508.3240676 · Cited by 9
QoE-driven HAS Live Video Channel Placement in the Media Cloud
Liu, J., Zhang, W., Huang, S., Du, H., & Zheng, Q. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.2999176 · Cited by 9
Preference-Aware Dynamic Bitrate Adaptation for Mobile Short-Form Video Feed Streaming
Ran, D., Hong, H., Chen, Y., Ma, B., Zhang, Y., Zhao, P., & Bian, K. (2020) · IEEE Access · doi:10.1109/access.2020.3042619 · Cited by 9
Scheduling in IEEE 802.15.4e Time Slotted Channel Hopping: A Survey
Hammoudi, S., Bentaleb, A., Harous, S., & Aliouat, Z. (2020) · IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · doi:10.1109/uemcon51285.2020.9298043 · Cited by 9
Self-citationOn Maximizing QoE in AVC-Based HTTP Adaptive Streaming: An SDN Approach
Erfanian, A., Tashtarian, F., & Yaghmaee, M. H. (2018) · International Workshop on Quality of Service · doi:10.1109/iwqos.2018.8624161 · Cited by 9
Ma, X., Li, Q., Chai, J., Xiao, X., Xia, S., & Jiang, Y. (2019) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3304112.3325603 · Cited by 9
An Efficient QoE-Aware HTTP Adaptive Streaming over Software Defined Networking
Thinh, P. H., Nguyen, D. T., Nam, P. N., Thanh, N. H., Nguyen, H. M., & Hương, T. T. (2020) · Mobile Networks and Applications · doi:10.1007/s11036-020-01543-1 · Cited by 9
QoE Management of Multimedia Services Using Machine Learning in SDN/NFV 5G Networks
Barakabitze, A. A., & Hines, A. (2022) · doi:10.1002/9781119800828.ch5 · Cited by 9
Huang, X., Li, C., Bentaleb, A., Zimmermann, R., & Zhai, G. (2023) · IEEE International Conference on Multimedia and Expo workshops · doi:10.1109/icmew59549.2023.00081 · Cited by 8
Self-citationDesign of a layer-based video streaming system over software-defined networks
Kalan, R. S., Çetinkaya, C., & Sayit, M. F. (2017) · International Conference on the Network of the Future (NOF) · doi:10.1109/nof.2017.8251213 · Cited by 8
Online Server-Side Optimization Approach for Improving QoE of DASH Clients
Marai, O. E., & Taleb, T. (2017) · Globecom · doi:10.1109/glocom.2017.8254128 · Cited by 8
Slow but Steady: Cap-Based Client-Network Interaction for Improved Streaming Experience
Krishnamoorthi, V., Carlsson, N. F., & Halepovic, E. (2018) · International Workshop on Quality of Service · doi:10.1109/iwqos.2018.8624170 · Cited by 8
Evaluation of Shared Resource Allocation Using SAND for ABR Streaming
Pham, S., Heeren, P., Schmidt, C., Silhavy, D., & Arbanowski, S. (2020) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3388926 · Cited by 8
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video Streaming Quality
Peroni, L., Gorinsky, S., Tashtarian, F., & Timmerer, C. (2023) · Proceedings of the ACM on Networking · doi:10.1145/3629139 · Cited by 7
QoE-based Load Balancing of OTT Video Content in SDN Networks
Oliveira, T., & Sargento, S. (2019) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc47284.2019.8969720 · Cited by 7
Chunk Duration--Aware SDN-Assisted DASH
Ozcelik, I. M., & Ersoy, C. (2019) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3337681 · Cited by 7
Storck, C. R., & Duarte-Figueiredo, F. (2020) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc50000.2020.9219682 · Cited by 7
TSBG: A Two-Stage Stackelberg Game Algorithm for QoE-Awareness Video Streaming Transmission
Xiang, S., Rong, H., Chen, J., Liu, D., & Jiang, H. (2024) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2024.3412860 · Cited by 6
Client-driven Adaptive Bitrate Techniques for Media Streaming over HTTP: Initial Findings
Khan, M. J., Harous, S., & Bentaleb, A. (2020) · IEEE International Conference on Electro Information Technology · doi:10.1109/eit48999.2020.9208253 · Cited by 6
Self-citationA simple yet effective network-assisted signal for enhanced DASH quality of experience
Samain, J., Carofiglio, G., Tortelli, M., & Rossi, D. (2018) · doi:10.1145/3210445.3210447 · Cited by 6
Begen, A. C. (2021) · Applied Networking Research Workshop (ANRW) · doi:10.1145/3472305.3472886 · Cited by 6
Self-citationA Quality-of-Experience Database for Adaptive Omnidirectional Video Streaming
Liu, X., Yan, J., Wan, Z., Fang, Y., & Wang, Z. (2023) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2023.3300529 · Cited by 6
Wang, K., Bao, Z., Liu, K., Liang, H., Dong, C., Xu, X., & Li, L. (2025) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2025.3563257 · Cited by 6
Quality of Experience in Video Streaming: Status Quo, Pitfalls, and Guidelines
Peroni, L., & Gorinsky, S. (2024) · International Conference on Communication Systems & Networks (COMSNETS) · doi:10.1109/comsnets59351.2024.10427330 · Cited by 5
Metadata
- Authors
- Bentaleb, A., Begen, A. C., & Zimmermann, R.
- Affiliations
- National University of Singapore (SG)
- Özyeğin University (TR)
- Venue
- Proceedings of the 24th ACM international conference on Multimedia
- Publisher
- ACM
- Published
- 2016-10
- Pages
- 1296-1305
- OpenAlex
- W2526384825
- Cited by
- 160
- References
- 18
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 11 · 2023: 10 · 2022: 15 · 2021: 16 · 2020: 28 · 2019: 25 · 2018: 34 · 2017: 12
- FWCI
- 20.22
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM International Conference on Multimedia (ACM MM) (publishedVersion)
- eResearch@Ozyegin (submittedVersion)
- Funders
- National University of Singapore (T1251RES/4/5)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Keywords
- HTTP adaptive streaming, software-defined networking, bandwidth competition, quality of experience, dynamic resource allocation, scalability, video streaming, network resource management
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
