International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

What Happens when Stochastic Adaptive Video Streaming Players Share a Bottleneck Link?


Affiliations
1 Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago
 

Competition among adaptive video streaming players severely diminishes user-QoE. When players compete at a bottleneck link many do not obtain adequate resources. This imbalance eventually causes ill effects such as screen flickering and video stalling. There have been many attempts in recent years to overcome some of these problems. This work focuses on such a situation. It evaluates current stochastic adaptive video players at a bottleneck link and when the number of players increases. Experimental setup includes the TAPAS player and emulated network conditions. The results show mDASH outperforms x-MDP, sdpDASH and the Conventional players.

Keywords

Adaptive Video Streaming, Bottleneck, Flickering, Stalling, TAPAS, mDASH, x-MDP, spdDASH.
User
Notifications
Font Size

  • Akhshabi, Saamer, Lakshmi Anantakrishnan, Ali C. Begen, and Constantine Dovrolis. "What happens when HTTP adaptive streaming players compete for bandwidth?." In Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video, pp. 9-14. ACM, 2012.

  • Andelin, T., V. Chetty, D. Harbaugh, S. Warnick, and D. Zappala (2012). Quality selection for dynamic adaptive streaming over http with scalable video coding. In Proceedings of the 3rd Multimedia Systems Conference, pp. 149-154. ACM.

  • Bertsekas, D. P., D. P. Bertsekas, D. P. Bertsekas, and D. P. Bertsekas (1995). Dynamic programming and optimal control, Volume 1. Athena scientic Belmont, MA.

  • Bokani, Ayub, Mahbub Hassan, and Salil Kanhere. "HTTP-based adaptive streaming for mobile clients using Markov decision process." In Packet Video Workshop (PV), 2013 20th International, pp. 1-8. IEEE, 2013.

  • Borgonovo, E. (2017). Cdf-based sensitivity measures. In Sensitivity Analysis, pp. 181189. Springer.

  • Boutilier, C., R. Dearden, and M. Goldszmidt (2000). Stochastic dynamic programming with factored representations. Articial intelligence 121(1), 49-107.

  • Chen, C., X. Zhu, G. de Veciana, A. C. Bovik, and R. W. Heath (2015). Rate adaptation and admission control for video transmission with subjective quality constraints. IEEE Journal of Selected Topics in Signal Processing 9(1), 22-36.

  • Chou, P. A. and Z. Miao (2006). Rate-distortion optimized streaming of packetized media. IEEE Transactions on Multimedia 8(2), 390-404.

  • De Cicco, Luca, Vito Caldaralo, Vittorio Palmisano, and Saverio Mascolo. "Elastic: a client-side controller for dynamic adaptive streaming over http (dash)." In Packet Video Workshop (PV), 2013 20th International, pp. 1-8. IEEE, 2013.

  • De Cicco, Luca, Vito Caldaralo, Vittorio Palmisano, and Saverio Mascolo. "TAPAS: a Tool for rApid Prototyping of Adaptive Streaming algorithms." In Proceedings of the 2014 Workshop on Design, Quality and Deployment of Adaptive Video Streaming, pp. 1-6. ACM, 2014.

  • Deshpande, P., X. Hou, and S. R. Das (2010). Performance comparison of 3g and metro-scale wifor vehicular network access. In Proceedings of the 10th ACM SIGCOMM conference on Internet measurement, pp. 301-307. ACM.

  • Garcia, Sergio, Julián Cabrera, and Narciso García. "Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming." In Consumer Electronics (ICCE), 2014 IEEE International Conference on, pp. 574-575. IEEE, 2014.

  • Jarnikov, Dmitri, and Tanır Özçelebi. "Client intelligence for adaptive streaming solutions." Signal Processing: Image Communication 26, no. 7 (2011): 378-389.

  • Khan, Koffka, and Wayne Goodridge. "Markov Decision Processes for bitrate harmony in adaptive video streaming." In 2017 Future Technologies Conference (FTC), Vancouver, Canada, unpublished.

  • Khan, Koffka, and Wayne Goodridge. "QoE in DASH." International Journal of Advanced Networking and Applications 9, no. 4 (2018): 3515-3522.

  • Khan, Koffka, and Wayne Goodridge. "Server-based and network-assisted solutions for adaptive video streaming." International Journal of Advanced Networking and Applications 9, no. 3 (2017): 3432-3442.

  • Khan, Koffka, and Wayne Goodridge. "S-MDP: Streaming with Markov Decision Processes." IEEE Transactions on Multimedia (2019).

  • Khan, Koffka, and Wayne Goodridge. "Variants of the Constrained Bottleneck LAN Edge Link in Household Networks." International Journal of Advanced Networking and Applications 10, no. 5 (2019): 4035-4044.

  • Marbach, Peter, and John N. Tsitsiklis. "Simulation-based optimization of Markov reward processes." IEEE Transactions on Automatic Control 46, no. 2 (2001): 191-209.

  • Mastronarde, N., K. Kanoun, D. Atienza, P. Frossard, and M. Van Der Schaar (2013). Markov decision process based energy-e-cient on-line scheduling for slice-parallel video decoders on multicore systems. IEEE transactions on multimedia 15(2), 268-278.

  • Ross, S. M. (2014). Introduction to stochastic dynamic programming. Academic press.

  • Steinbach, E., N. Farber, and B. Girod (2001). Adaptive playout for low latency video streaming. In Image Processing, 2001. Proceedings. 2001 International Conference on, Volume 1, pp. 962-965. IEEE.

  • Wang, Bing, Jim Kurose, Prashant Shenoy, and Don Towsley. "Multimedia streaming via TCP: An analytic performance study." In Proceedings of the 12th annual ACM international conference on Multimedia, pp. 908-915. ACM, 2004.

  • Xiang, S., L. Cai, and J. Pan (2012). Adaptive scalable video streaming in wireless networks. In Proceedings of the 3rd multimedia systems conference, pp. 167-172. ACM.

  • Xing, M., S. Xiang, and L. Cai (2012). Rate adaptation strategy for video streaming over multiple wireless access networks. In Global Communications Conference (GLOBECOM), 2012 IEEE, pp. 5745-5750. IEEE.

  • Xing, M., S. Xiang, and L. Cai (2014). A real-time adaptive algorithm for video streaming over multiple wireless access networks. IEEE Journal on Selected Areas in communications 32(4), 795-805.

  • Yao, J., S. S. Kanhere, and M. Hassan (2008). An empirical study of bandwidth predictability in mobile computing. In Proceedings of the third ACM inter national workshop on Wireless network testbeds, experimental evaluation and characterization, pp. 11-18. ACM.

  • Zhou, Chao, Chia-Wen Lin, and Zongming Guo. "mDASH: A Markov decision-based rate adaptation approach for dynamic HTTP streaming." IEEE Transactions on Multimedia 18, no. 4 (2016): 738-751.


Abstract Views: 282

PDF Views: 0




  • What Happens when Stochastic Adaptive Video Streaming Players Share a Bottleneck Link?

Abstract Views: 282  |  PDF Views: 0

Authors

Koffka Khan
Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago
Wayne Goodridge
Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago

Abstract


Competition among adaptive video streaming players severely diminishes user-QoE. When players compete at a bottleneck link many do not obtain adequate resources. This imbalance eventually causes ill effects such as screen flickering and video stalling. There have been many attempts in recent years to overcome some of these problems. This work focuses on such a situation. It evaluates current stochastic adaptive video players at a bottleneck link and when the number of players increases. Experimental setup includes the TAPAS player and emulated network conditions. The results show mDASH outperforms x-MDP, sdpDASH and the Conventional players.

Keywords


Adaptive Video Streaming, Bottleneck, Flickering, Stalling, TAPAS, mDASH, x-MDP, spdDASH.

References