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iVID: An Internet Infrastructure for Video Streaming Optimisation

iVID: An Internet Infrastructure for Video Streaming Optimisation

Principal Investigator:

 

Research Team:

 

Collaborators: 

 

Short descripton: 

Media streaming services, such as IPTV, Video-On-Demand (VOD), and video calling, continue to emerge requiring more and more network resources.For example, several studies predict that mobile video data traffic would increase 15-20 times by 2018. This demand increase affects the quality of service of video streaming sessions resulting in problems such as interrupted streaming, large session setup delay, and reduced video quality. Many of the existing solutions solely depend on end-to-end quality improvement approaches. Recently, Software-Defined Networks (SDNs) promise a high degree of flexibility in network control, providing an impetus to consider network-oriented solutions for improving video streaming performance. Our research aim is the design of suitable network control enhancements, to analyse their operational behaviour, and to evaluate their impact on user quality of experience and network resource utilisation.  Our  hypothesis  is that solving these problems requires a coordinated network system capable of controlling and optimising video delivery to end-users. Solutions that are exclusively client-side or server-side struggle to infer a sufficiently accurate view of the network resource. Our approach exposes the network state, allowing a managed response to video delivery.
 
 

Awards: 

SAP: Stall-Aware Pacing for Improved DASH Video Experience in Cellular Networks. Winner of the "Excellence in DASH Award". Proc. of ACM Multimedia Systems 2017, Taipei, Taiwan, June 20-23, 2017. For further details click here.
 
D-LiTE: A platform for evaluating DASH performance over a simulated LTE network. "Best Demo Award". Proc. of 22nd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2016), Rome, Italy. June 13-15, 2016. For further details click here.
 
 

Demos, Datasets and Software:

D-LiTE:  http://www.cs.ucc.ie/misl/research/software/lanman2016/ 

D-LiTE-ful: http://www.cs.ucc.ie/misl/research/software/wintech2016/ 

MiniNAM: http://www.cs.ucc.ie/misl/research/software/mininam/ 

LCN Demo: http://www.cs.ucc.ie/misl/research/software/lcn2017/

AVC and HEVC Full HD DASH Datasets: http://www.cs.ucc.ie/misl/research/datasets/ivid_dataset/

SAP: http://www.cs.ucc.ie/misl/research/software/sap-testbed/

AVC and HEVC UHD 4K DASH Datasets: http://www.cs.ucc.ie/misl/research/datasets/ivid_uhd_dataset/

4G LTE Dataset: http://www.cs.ucc.ie/misl/research/datasets/ivid_4g_lte_dataset/

 

Publications:

The following publications can be accessed from the relevant conference publishers (ACM/IEEE/MDPI) or from CORA. CORA is the Cork Open Research Archive and gives you free open access to University College Cork's scholarly and scientific research publications and theses.
 

A. Khalid, A.H. Zahran, and C.J. Sreenan. An SDN-Based Device-Aware Live Video Service For Inter-Domain Adaptive Bitrate Streaming. ACM Multimedia Systems Conference (MMSys), June 18-21 2019 (To Appear).

A. Khalid, A.H. Zahran, and C.J. Sreenan. RTOP: Optimal User Grouping and SFN Clustering for Multiple eMBMS Video Sessions. Proc. of the IEEE International Conference on Computer Communications (INFOCOM). 29 April- 2 May 2019, Paris, France. (To Appear).

A.H. Zahran, J.J. Quinlan, K.K. Ramakrishnan, C.J. Sreenan. ASAP: Adaptive Stall-Aware Pacing for Improved DASH Video Experience in Cellular Networks. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). Vol. 14(3s), pp. 61, June 2018. [CORA] [ACM]

D. Raca, A.H. Zahran, C.J. Sreenan R.K. Sinha, E. Halepovic, R. Jana, V. Gopalakrishnan, B. Bathula, M. Varvello. Incorporating Prediction into Adaptive Streaming Algorithms: A QoE Perspective. Proc. of 28th ACM SIGMM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV'18), Amsterdam, The Netherlands, June 2018. [CORA] [ACM]

D. Raca, J.J. Quinlan, A.H. Zahran, C.J. Sreenan. Beyond Throughput: a 4G LTE Dataset with Channel and Context Metrics. Proc. of ACM Multimedia Systems Conference (MMSys 2018), Amsterdam, The Netherlands, June 2018. [CORA] [ACM]

J.J. Quinlan, C.J. Sreenan. Multi-Profile Ultra High Definition (UHD) AVC and HEVC 4K DASH Datasets [Poster]. Proc. of ACM Multimedia Systems Conference (MMSys 2018), Amsterdam, The Netherlands, June 2018. [CORA] [ACM]

A. Reviakin, A.H. Zahran, C.J. Sreenan. dashc : a highly scalable client emulator for DASH video. Proc. of ACM Multimedia Systems Conference (MMSys 2018), Amsterdam, The Netherlands, June 2018. [CORA] [ACM]

A.H. Zahran, D. Raca, C.J. Sreenan. ARBITER+: Adaptive Rate-Based InTElligent HTTP StReaming Algorithm for Mobile Networks. IEEE Transactions on Mobile Computing. PP 1-1. (DOI: 10.1109/TMC.2018.2825384), April 2018. [CORA] [IEEE]

J.J. Quinlan, A.H. Zahran, C.J. Sreenan. Efficient Delivery of Scalable Video using a Streaming Class Model. Invited publication in the Special Issue of “Information” on Network and Rateless Coding for Video Streaming. Information 2018, 9(3), 59. March 2018 [CORA] [MDPI]

J.J. Quinlan. SDaN: Software Defined adaptive Networking - IoT and beyond. [Presentation] Proc of the MadCom Workshop: New Wireless Communication Paradigms for the Internet of Things @ the International Conference on Embedded Wireless Systems and Networks (EWSN) 2018, Madrid, Spain, February 14-16, 2018. [CORA] [ACM]

D. Raca, A.H. Zahran, C.J. Sreenan, R.K. Sinha, E. Halepovic, R. Jana, V. Gopalakrishnan. Back to the Future: Throughput Prediction For Cellular Networks using Radio KPIs. Proc of 4th ACM Workshop on Hot Topics in Wireless (HotWireless 2017) at the ACM MobiCom Conference, October 16-20, 2017, Utah, USA. [CORA] [ACM]

A. Khalid, A.H. Zahran, C.J. Sreenan. mCast: An SDN-based Resource-Efficient Live Video Streaming Architecture with ISP-CDN Collaboration. [Presentation] Proc of the 42nd IEEE Conference on Local Computer Networks (LCN), October 9-12, 2017, Singapore. [CORA] [IEEE]

A. Khalid, A.H. Zahran, C.J. Sreenan. DEMO: Prototyping and Evaluating SDN-based Multicast Architectures for Live Video Streaming. [Poster] Proc of the 42nd IEEE Conference on Local Computer Networks (LCN), October 9-12, 2017, Singapore. [CORA_Demo] [CORA_Poster][IEEE]

A.H. Zahran, J.J. Quinlan, K. K. Ramakrishnan, C.J. Sreenan. SAP: Stall-Aware Pacing for Improved DASH Video Experience in Cellular Networks. [Presentation] Proc. of ACM Multimedia Systems 2017, Taipei, Taiwan, June 20-23, 2017. (Winner of the "Excellence in DASH Award"). [CORA] [ACM]

A. Khalid, J.J. Quinlan, C.J. Sreenan. MiniNAM: A Network Animator for Visualizing Real-Time Packet Flows in Mininet. [Poster] Proc of the 20th conference on Innovations in Clouds, Internet and Networks, ICIN2017, Paris, France, March 7 - 9, 2017. [CORA] [IEEE] 

J.J. Quinlan, A. Reviakin, A. Khalid, K.K. Ramakrishnan, C.J. Sreenan. D-LiTE-ful: An evaluation platform for DASH QoE for SDN-enabled ISP offloading in LTE. [Presentation] Proc of the 10th ACM International Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization (WINTECH) at the ACM MobiCom Conference, October 2016. [CORA] [ACM]

D. Raca, A.H. Zahran, C.J. Sreenan. Sizing Network Buffers: A HTTP Adaptive Streaming Perspective. [Presentation] Proc. of 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, Austria. August 22-24, 2016. [CORA] [IEEE] 

A.H. Zahran, C.J. Sreenan. ARBITER: Adaptive Rate-Based InTElligent HTTP StReaming Algorithm. [Presentation] Proc. of 22rd International Packet Video Workshop (PV 2016), Seattle, WA, USA. July 11-15, 2016. [CORA] [IEEE]

J.J. Quinlan, D. Raca, A.H. Zahran, A. Khalid, K.K. Ramakrishnan,C.J. Sreenan. DEMO: D-LiTE: A platform for evaluating DASH performance over a simulated LTE network. [Presentation] Proc. of 22nd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2016), Rome, Italy. June 13-15, 2016. (Best Demo Award). [CORA] [IEEE]

A.H. Zahran, J.J. Quinlan, C.J. Sreenan, K.K. Ramakrishnan. Impact of the LTE Scheduler on achieving Good QoE for DASH Video Streaming. [Presentation] Proc. of 22nd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2016), Rome, Italy. June 13-15, 2016. [CORA] [IEEE]

J.J. Quinlan, A.H. Zahran, C.J. Sreenan. Datasets for AVC (H.264) and HEVC (H.265) Evaluation of Dynamic Adaptive Streaming over HTTP (DASH). [Presentation] Proc. of the 7th ACM Multimedia Systems Conference 2016 (MMSYS 2016), Klagenfurt am Wörthersee, Austria. May 10-13, 2016. [CORA] [ACM]

A.H. Zahran, J.J. Quinlan, D. Raca, C.J. Sreenan, E. Halepovic, R. K. Sinha, R. Jana, V. Gopalakrishnan. OSCAR: An Optimized Stall-Cautious Adaptive Bitrate Streaming Algorithm For Mobile Networks. [Presentation] Proc. of the 8th ACM Workshop on Mobile Video. (MoVid 2016), Klagenfurt am Wörthersee, Austria. May 10-13, 2016. [CORA] [ACM]

M.K. Abdel-Aziz, A.H. Zahran, T. ElBatt. A Novel Framework For Scalable Video Streaming Over Multi-Channel Multi-Radio Wireless Mesh Networks. [Presentation] Proc. 8th ACM workshop on Mobile Video, (MoVid 2016), Klagenfurt, Klagenfurt am Wörthersee, Austria. May 10-13, 2016. [ACM]

J.J. Quinlan, A.H. Zahran, K.K. Ramakrishnan, C.J. Sreenan. Delivery of Adaptive Bit Rate Video: Balancing Fairness, Efficiency and Quality. [Presentation] Proc. of 21st IEEE International Workshop on Local and Metropolitan Area Networks (LANMAN), Tsinghua, Beijing, China. April 22-24 2015. [CORA] [IEEE]

 

Groups influenced by our work include:

Via Citations:
University of Missouri, Kansas City, USA
National University of Sciences & Technology, Pakistan
Pierre and Marie Curie University, Paris, France
Universite De Rennes, France
Koç University, Istanbul, Turkey
Petrozavodsk State University, Russia
University of Kocaeli, Kocaeli, Turkey
Universidad Politécnica de Valencia, Spain
University of Roma “Sapienza”, Rome, Italy
Technische Universität Berlin, Berlin, Germany
American University of Beirut (AUB), Beirut, Lebanon
Qatar Mobility Innovation Center (QMIC), Doha, Qatar
IMDEA Networks Institute, Madrid, Spain
Politecnico di Milano, Milano, Italy
NYU Tandon School of Engineering, Brooklyn, NY
Nokia Bell Labs, Stuttgart, Germany
Dept. of Computer Engineering, Mugla Sitki Kocman University, Mugla, Turkey
TU Dortmund University, Dortmund, Germany
Columbia University, New York, US
Ege University, Izmir, Turkey
Institute of Technology Kharagpur, India
Alpen-Adria-Universität Klagenfurt, Austria
Dept. of Electrical and Electronics Engineering, TED University, Ankara, Turkey
Bitmovin Inc., California, USA
Linkoping University, Sweden
School of Communication and Information Engineering (SCIE), University of Electronic Science and Technology of China
National University of Singapore, Singapore
Ozyegin University and Networked Media, Istanbul, Turkey
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
Delft University of Technology Amsterdam, The Netherlands
Dipartimento di Elettronica Informazione e Bioingegneria (DEIB), Italy
Dept. of Electrical and Electronics Engineering, TOBB University of Economics and
Technology, Ankara, Turkey 
 
Via Software usage:
University of California, Riverside
National and Kapodistrian University of Athens, Greece
Plymouth University, UK
Huawei German Research Center
University of Aalen, Germany
Tsinghua University, China
University of Aberdeen, UK 

Publicity:

Research bid to make slow streaming a thing of the past, Irish Examiner, 5th May 2014: 
 
Research riches: what we get for our money, Irish Times, 26th June 2014: 
 
Scientific research projects awarded €47 million, Irish Times, 17th October 2014: 
 
Focus on research: Prof Cormac Sreenan, Connect, techcentral.ie, 26th September 2016: 

 

Sponsor:

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Mobile and Internet Systems Laboratory

Department of Computer Science, Western Gateway Building, University College Cork, Western Road, Cork, Ireland.

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