dash

This program is my backelor's degree program based on djvergad/dash.

Multi-DASH streaming behavior analysis and optimization beased on Reinforcement Learning.

An MPEG/DASH client-server ns3 module for simulating rate adaptation algorithms over HTTP/TCP.

This module was built for generating the simulation results in the following papers:

• Dimitrios J. Vergados, Angelos Michalas, Aggeliki Sgora, Dimitrios D. Vergados, and Periklis Chatzimisios. "FDASH: A Fuzzy-Based MPEG/DASH Adaptation Algorithm." IEEE Systems Journal 10, no. 2 (2016): 859-868.
• Dimitrios J. Vergados, Angelos Michalas, Aggeliki Sgora, and Dimitrios D. Vergados. "A fuzzy controller for rate adaptation in MPEG-DASH clients." In 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), pp. 2008-2012. IEEE, 2014.
• Dimitrios J. Vergados, Angelos Michalas, Aggeliki Sgora, and Dimitrios D. Vergados. "A control-based algorithm for rate adaption in MPEG-DASH." In Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference on, pp. 438-442. IEEE, 2014.

The DASH rate adaptation algorithms that are implemented are the following:

• FDASH, This is the algorithms that is proposed in the above papers
• AAASH, presented in: K. Miller, E. Quacchio, G. Gennari, and A. Wolisz, “Adaptation algorithm for adaptive streaming over HTTP,” in Proc. 19th Int. IEEE PV Workshop, 2012, pp. 173–178.
• OSMF, presented in: R. K. P. Mok, X. Luo, E. W. W. Chan, and R. K. C. Chang, “QDASH: A QoE-aware DASH system,” in Proc. 3rd MMSys Conf., New York, NY, USA, 2012, pp. 11–22.
• SVAA, presented in: G. Tian and Y. Liu, “Towards agile and smooth video adaptation in dynamic HTTP streaming,” in Proc. 8th Int. CoNEXT, New York, NY, USA, 2012, pp. 109–120. [Online].
• RAAHS, presented in: C. Liu, I. Bouazizi, and M. Gabbouj, “Rate adaptation for adaptive HTTP streaming,” in Proc. 2nd Annu. ACM Conf. MMSys, New York, NY, USA, 2011, pp. 169–174. [Online].
• SFTM, presented in: C. Liu, I. Bouazizi, M. M. Hannuksela, and M. Gabbouj, “Rate adaptation for dynamic adaptive streaming over HTTP in content distribution network,” Signal Process., Image Commun., vol. 27, no. 4, pp. 288–311, Apr. 2012.
• MPC, presented in: X. Yin, A. Jindal, V. Sekar, and B. Sinopoli. 2015. A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP. In SIGCOMM. ACM. -****** BB, presented in: T.Y. Huang et al. 2014. A Buffer-based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service. In SIGCOMM. ACM. -****** pensieve, presented in: H.Z. Mao et al. 2017. Neural Adaptive Video Streaming with Pensieve. In SIGCOMM. ACM. Installation instructions

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1. Install ns3 on you system, using the instructions like from here: https://www.nsnam.org/wiki/Installation#Downloading_ns-3_Using_Mercurial.

2. Download the module into the src directory, with the following commands:

   cd ns-3-dev/
   cd src/
   git clone https://github.com/djvergad/dash.git
   

   A new directory named dash should be created in the src directory

3. Re-configure ns3 and enable examples. From the ns-3-dev directory, type:

   ./waf configure --enable-examples
   

4. Now the setup is complete. Validate by running an example:

   ./waf --run 'src/dash/examples/dash-example --users=3 --protocol="ns3::FdashClient" --linkRate=1000Kbps'
   

   There should be output similar to the following:

   0.829568 Node: 0 newBitRate: 89000 oldBitRate: 45000 estBitRate: 205177 interTime: 0 T: 1.4284 dT: 0 del: +0.0ns
   0.84288 Node: 1 newBitRate: 89000 oldBitRate: 45000 estBitRate: 197645 interTime: 0 T: 1.42024 dT: 0 del: +0.0ns
   0.849848 Node: 2 newBitRate: 89000 oldBitRate: 45000 estBitRate: 185404 interTime: 0 T: 1.41842 dT: 0 del: +0.0ns
   1.40569 Node: 0 newBitRate: 131000 oldBitRate: 89000 estBitRate: 276525 interTime: 0 T: 2.85228 dT: 1.42388 del: +0.0ns
   1.45575 Node: 1 newBitRate: 131000 oldBitRate: 89000 estBitRate: 261727 interTime: 0 T: 2.80737 dT: 1.38713 del: +0.0ns
   1.51679 Node: 2 newBitRate: 89000 oldBitRate: 89000 estBitRate: 246766 interTime: 0 T: 2.75148 dT: 1.33306 del: +0.0ns
   ...
   95.931 Node: 0 newBitRate: 396000 oldBitRate: 396000 estBitRate: 427899 interTime: 0 T: 38.3269 dT: 0.175848 del: +0.0ns
   96.5143 Node: 1 newBitRate: 263000 oldBitRate: 263000 estBitRate: 282589 interTime: 0 T: 37.7488 dT: 0.139504 del: +0.0ns
   96.9279 Node: 2 newBitRate: 178000 oldBitRate: 178000 estBitRate: 197848 interTime: 0 T: 37.3404 dT: 0.12356 del: +0.0ns
   97.7929 Node: 0 newBitRate: 396000 oldBitRate: 396000 estBitRate: 424918 interTime: 0 T: 38.4651 dT: 0.138144 del: +0.0ns
   98.2967 Node: 1 newBitRate: 263000 oldBitRate: 263000 estBitRate: 275899 interTime: 0 T: 37.9664 dT: 0.217576 del: +0.0ns
   98.6872 Node: 2 newBitRate: 178000 oldBitRate: 178000 estBitRate: 200443 interTime: 0 T: 37.581 dT: 0.240664 del: +0.0ns
   99.5082 Node: 0 newBitRate: 396000 oldBitRate: 396000 estBitRate: 426879 interTime: 0 T: 38.7498 dT: 0.284736 del: +0.0ns
   ns3::FdashClient-Node: 0 InterruptionTime: 0 interruptions: 0 avgRate: 248101 minRate: 89000 AvgDt: 38.4632 changes: 7
   ns3::FdashClient-Node: 1 InterruptionTime: 0 interruptions: 0 avgRate: 175772 minRate: 89000 AvgDt: 37.577 changes: 5
   ns3::FdashClient-Node: 2 InterruptionTime: 0 interruptions: 0 avgRate: 120478 minRate: 89000 AvgDt: 36.4311 changes: 3