Network Coding and Media Streaming (Invited Paper)
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Network Coding and Media Streaming(Invited Paper)
Nikolaos Thomos and Pascal Frossard
Signal Processing Laboratory (LTS4)Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland
JOURNAL OF COMMUNICATIONS, VOL. 4, NO. 9, OCTOBER 2009
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OutlineIntroductionNetwork codingNetwork coding in streaming applicationConclusion
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IntroductionThis paper
describes the potentials of network coding in emerging delivery architectures such as overlay or peer-to-peer networks.
overviews the principles of practical network coding algorithms and outlines the challenges posed by multimedia streaming applications
provides a survey of the recent work on the application of network coding to media streaming applications
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Network CodingNetwork coding has recently emerged as an
alternative to traditional routing algorithms in communication systems.
Pioneering work: [2] R. Ahlswede, N. Cai, S.-Y. R. Li, and R.W. Yeung, “Network information flow,” IEEE Trans. on Information Theory, vol. 46, no. 4, July 2000.
Improves the performance in data broadcasting Most suitable setting: all to all communications
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S1 S2
C2C1
b1
b1b1
b2
b2
b2
b2
b1
S1 S2
C2C1
b1
b1
b2
b2b1+b2
b1+b2b1+b2
(a) Traditional routing algorithm
(b) Network coding
The Butterfly Network
The average throughput = 3/2 Need transmission schedule.
The average throughput = 2 No transmission schedule.
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Wireless relay networks1. Only 3 transmissions, and2. reduce the energy consumption of the antenna.
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Error-prone tandem network𝜀𝑆1 𝑅1 𝜀𝑅1𝐶 1
𝜀𝑆2𝑅1
S1 to C1S1 to C1
R1 can encode and decode
packet
Add S2 to network.
Communication rate (1-) (1-) min{(1-), (1-)}
min{max{(1-), (1-)} , (1-)}
: loss rate over the link ij.
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Linear Network CodingLinear network coding [21] is probably the most
successful network coding algorithm due to its relatively low complexity and ability to achieve network capacity in multicast problems.
[21] S.-Y. R. Li, R. W. Yeung, and N. Cai, “Linear Network Coding,” IEEE Trans. Information Theory, vol. 49, no. 2, pp. 371–381, Feb. 2003.
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Linear Network Coding When we refer to linear network coding [21], we intend that:
Coding can be implemented at low computational cost
Moreover, the information traversing a non source node has the following property:
The output flow at a given node is obtained as a linear combination of its input flows. The coefficients of the combination are,
by definition, selected from a finite field
The content of any information flowing out of a set of non source nodes can be derived from the accumulated information that has
flown into the set of nodes
[21] S.-Y. R. Li, R. W. Yeung, and N. Cai, “Linear Network Coding,” IEEE Trans. Information Theory, vol. 49, no. 2, pp. 371–381, Feb. 2003.
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Theoretical model for Linear NCA directed, acyclic graph G(V,E) have unit-
capacity edges.Parallel edges are allowed.A message is represented as symbols in a finite
field F, and encoding/decoding is by means of linear operations in the finite field.
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Local Description of Linear NCDefine the local encoding kernel of a-dimensional
network code at node t as a matrix of size .
• : the set of incoming links of node t.• : the set of outgoing links of node t.
The local input-output relation at a node T is given by
is the symbol sent on the channel e.i.e., an output symbol from T is a linear combination
of the input symbols at T.
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Global Description of a Linear NCThe code maps the information vector x to
each symbol sent on the channel e. is called global encoding kernel.
The global description of linear NC
The global description of a linear network code incorporates the local description.
as in the local description.
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Example of Linear NC
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Desirable Properties of a Linear NC[10]
we have.
An ω-dimensional F F-valued linear network code qualifies as a Linear multicast for every non source node t with . Linear broadcast for every non source node t. Linear dispersion for any set T of non source nodes.
,
[10] R. W. Yeung, Information Theory and Network Coding, ser. Information Technology: Transmission, Processing and Storage. Springer-Verlag, 2008.
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Linear Network CodingThe construction of a linear code has to consider
both the value of and the network topology, along with the size of the base field F.
How to construct good linear network codes?The global encoding kernels to be as independent as
possible.Select proper coefficients such that all local
encoding kernels are full rank.
Several works have addressed the problem of the construction of good linear network codes.[23]-[29]
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Practical Network Coding[18]
The problem of theoretical linear NCDefining the coding coefficient uses
computationally complex algorithm.Servers have a full knowledge of network
topology.Linear NC is therefore not practical in large
scale dynamic network.Randomized Network Coding
The coefficient are randomly chosen in a sufficiently large Galois Field.
It permits to relax the requirements about the full knowledge of the network topology.
[18] P. A. Chou, Y. Wu, and K. Jain, “Practical Network Coding,” in Proc. of the 41st Allerton Conf. on Communication Control and Computing, Monticell, IL, USA, Oct. 2003.
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Practical Network Coding[18]
The author in [18] introduce the concept of generation. In order to cope with the buffer delay problem.A generation is a group of packets with similar
decoding deadlines, which can be combined together by the network coding operations.
Trade-off generation size(delay) v .s coding efficiency
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Network coding in streaming application
The design of the system has to take the following specificities into consideration.• Strict delay constraints• High bandwidth requirement• Tolerance packet loss• Unequal importance of the data
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Peer-to-Peer StreamingThe evaluation[36] shows that the network
coding scheme is resilient to network dynamics.
[36] M. Wang and B. Li, “Lava: A Reality Check of NetworkCoding in Peer-to-Peer Live Streaming,” in Proc. of IEEEINFOCOM, Anchorage, Alaska, May 2007.
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Peer-to-Peer Streaming The organization of the peers in the overlay network has a large
influence on the performance of the streaming system.
[39] K. Jain, L. Lovsz, and P. A. Chou, “Building Scalable and Robust Peer-to-Peer Overlay Networks for Broadcasting Using Network Coding,” Journal on Distributed Computing, vol. 19, no. 4, pp. 301–311, Dec. 2006.[40] J. Zhao, F. Yang, Q. Zhang, Z. Zhang, and F. Zhang, “LION: Layered Overlay Multicast With Network Coding,” IEEE Trans. Multimedia, vol. 8, no. 5, pp. 1021–1032, Oct. 2006.[41] Y. Liu, Y. Peng, W. Dou, and B. Guo, “Network Coding for Peer-to-Peer Live Media Streaming,” in Proc of the 5th Int. Conf. Grid and Cooperative Computing, Monticello, IL, USA, Oct. 2006, pp. 149–155.[42] M. Shao, X. Wu, and N. Sarshar, “Rainbow Network Flow with Network Coding,” in Proc. of the 4th Workshop on Network Coding, Theory and Applications, NetCod, Hong Kong, China, Jan 2008, pp. 1–6.
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Resiliency to Packet LossesThe media streaming system has to be robust
to packet erasures and maintain low delay for improved performance.
Network-embedded FEC(NEF)[43],[44]
[43] S. Karande, M. Wu, and H. Radha, “Network Embedded FEC (NEF) for Video Multicast in Presence of Packet Loss Correlation,” in Proc. of IEEE Int. Conf. on Image Processing, vol. 1, Genoa, Italy, Sep. 2005, pp. 173–176.[44] M. Wu, S. Karande, and H. Radha, “Network Embedded FEC for Optimum Throughput of Multicast Packet Video,” EURASIP Journal on Applied Signal Processing, vol. 20, no. 8, pp. 728–742, Sep. 2005.
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Prioritized Network CodingNetwork coding based on Prioritized Encoding
Transmission(PET)[34] can adapt to this property by handling the packets according to their priority.
[34] A. Albanese, J. Bloemer, J. Edmonds, M. Luby, and M. Sudan, “Priority Encoding Transmission,” IEEE Trans. Information Theory, vol. 42, pp. 1737–1744, Nov. 1996.
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Adaptively and Opportunistic CodingWhen packet transmission can be overheard
by multiple nodes, receivers could build up a buffer of packets that can be used to decode the successive packets.
The senders can thus use some knowledge about the receiver status to optimize network coding operations and reduce the overall transmission costs.
The COPE architecture has been presented in [58] for communication over wireless mesh networks.[58] S. Katti, H. Rahui, W. Hu, D. Katabi, M. M´edard, and J. Crowcroft, “XORs in the
air: practical wireless network coding,” in Proc of. ACM SIGCOMM, vol. 36, no. 4, New York, NY, USA, May 2006, pp. 243–254.
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Adaptively and Opportunistic Coding[58]
[58] S. Katti, H. Rahui, W. Hu, D. Katabi, M. M´edard, and J. Crowcroft, “XORs in the air: practical wireless network coding,” in Proc of. ACM SIGCOMM, vol. 36, no. 4, New York, NY, USA, May 2006, pp. 243–254.
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Conclusion Network coding is an interesting paradigm that
requests the network nodes to perform basic processing operations on packets in order to improve the throughput or the robustness of communication systems with network diversity.
There are still a few open issues to solve before network coding algorithms could be widely deployed in streaming applications. Decoding complexity is pretty high in the most of the
literature. Distributed algorithms require to transmit coding
information in the packet header, leading to overhead. The choice of the right trade-off between delay, coding
efficiency and complexity.