iVID: An Internet Infrastructure for Video Streaming Optimisation

Principal Investigator:

Research Team:


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.
Demos and Software

D-LiTE:  https://www.ucc.ie/en/misl/research/current/ivid_demo/lanman2016/

D-LiTE-ful: https://www.ucc.ie/en/misl/research/current/ivid_demo/wintech2016/

Datasets: http://www.ucc.ie/en/misl/research/current/ivid_dataset/

MiniNAM: https://www.ucc.ie/en/misl/research/current/ivid_demo/mininam/


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

A. KhalidJ.J. QuinlanC.J. SreenanMiniNAM: A Network Animator for Visualizing Real-Time Packet Flows in Mininet. Proc of the 20th conference on Innovations in Clouds, Internet and Networks, ICIN2017, Paris, France, March 7 - 9, 2017.

J.J. Quinlan, A. Reviakin, A. Khalid, K.K. Ramakrishnan, C.J. SreenanD-LiTE-ful: An evaluation platform for DASH QoE for SDN-enabled ISP offloading in LTE. [Presentation (3,731kB)] Proc of the 10th ACM International Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization (WINTECH) at the ACM MobiCom Conference, October 2016.

D. RacaA.H. ZahranC.J. Sreenan. Sizing Network Buffers: A HTTP Adaptive Streaming Perspective. [Presentation (5,000kB)] Proc. of 4th International Conference on Future Internet of Things and Cloud (FiCloud), Vienna, Austria. August 22-24, 2016. 

A.H. Zahran, and C.J. SreenanARBITER: Adaptive Rate-Based Intelligent HTTP StReaming Algorithm. [Presentation (3,075kB)] Proc. of 22rd International Packet Video Workshop (PV 2016), Seattle, WA, USA. July 11-15, 2016.

J.J. QuinlanD. RacaA.H. ZahranA. Khalid, K.K. Ramakrishnan,C.J. Sreenan. DEMO: D-LiTE: A platform for evaluating DASH performance over a simulated LTE network. [Presentation (3,821kB)] Proc. of 22nd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2016), Rome, Italy. June 13-15, 2016. (Best Demo Award).

A.H. ZahranJ.J. QuinlanC.J. Sreenan, K.K. Ramakrishnan. Impact of the LTE Scheduler on achieving Good QoE for DASH Video Streaming. [Presentation (1,976kB)] Proc. of 22nd IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN 2016), Rome, Italy. June 13-15, 2016. 

J.J. QuinlanA.H. ZahranC.J. Sreenan. Datasets for AVC (H.264) and HEVC (H.265) Evaluation of Dynamic Adaptive Streaming over HTTP (DASH). [Presentation (1,359kB)] Proc. of the 7th ACM Multimedia Systems Conference 2016 (MMSYS 2016), Klagenfurt am Wörthersee, Austria. May 10-13, 2016. 

A.H. ZahranJ.J. QuinlanD. RacaC.J. Sreenan, E. Halepovic, R. K. Sinha, R. Jana, V. Gopalakrishnan. OSCAR: An Optimized Stall-Cautious Adaptive Bitrate Streaming Algorithm For Mobile Networks. [Presentation (3,678kB)] Proc. of the 8th ACM Workshop on Mobile Video. (MoVid 2016), Klagenfurt am Wörthersee, Austria. May 10-13, 2016. 

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 (1,409kB) Proc. 8th ACM workshop on Mobile Video, (MoVid 2016), Klagenfurt, Klagenfurt am Wörthersee, Austria. May 10-13, 2016. 

J.J QuinlanA.H. Zahran, K.K. Ramakrishnan, C.J. Sreenan. Delivery of Adaptive Bit Rate Video: Balancing Fairness, Efficiency and Quality. [Presentation (1,265kB)] Proc. of 21st IEEE International Workshop on Local and Metropolitan Area Networks (LANMAN), Tsinghua, Beijing, China. April 22-24 2015.


Research bid to make slow streaming a thing of the past, Irish Examiner, 5th May 2014: http://www.irishexaminer.com/ireland/research-bid-to-make-slow-streaming-a-thing-of-the-past-267476.html

Research riches: what we get for our money, Irish Times, 26th June 2014: http://www.irishtimes.com/news/science/research-riches-what-we-get-for-our-money-1.1845017

Scientific research projects awarded €47 million, Irish Times, 17th October 2014: http://www.irishtimes.com/news/science/scientific-research-projects-awarded-47-million-1.1780030

Focus on research: Prof Cormac Sreenan, Connect, techcentral.ie, 26th September 2016: http://www.techcentral.ie/focus-on-research-prof-cormac-sreenan-connect/


Science Foundation Ireland 


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