jesse e. simsarian and marcus duelk bell laboratories, alcatel-lucent, holmdel, nj,...

Jesse E. Simsarian and Marcus Duelk

Bell Laboratories, Alcatel-Lucent, Holmdel, NJ, jesses@alcatel-lucent.com

15th IEEE Workshop on Local and Metropolitan Area Networks, 2007

Chen Bin Kuo (20077202)

Young J. Won (20063292)

DPNM Lab.

Introduction Data and Voice Traffic IPTV Network Architecture VoD Content and User Behavior Caching of Content Main Traffic Conclusion

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In the paper, authors analyze the bandwidth requirements in Metropolitan Area Networks (MANs) for providing IPTV services.

Developing a model of IPTV network to determine the optimum location of the cached video content.

Finding out the effect upon MAN traffic by users simultaneously requesting VoD streams

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DPNM Lab.

Applying previous work on content delivery to a realistic metropolitan area work (MAN) Previous work: unicast content delivery [1][2] , proxy server

method [3], and multicast groups [4][5] Considering a service provider is optimizing content

delivery

Assuming a small amount of buffering at the client’s set-top box Delivery stream is viewed nearly in real time Do not consider VoD multicast [4]

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Developed a cost model of the total network including: The servers that cache the on-demand video Costs associated with data switching and transport

Reporting the results about future MAN traffic

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a) Voice Trafficb) Data Traffic

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DPNM Lab.

Voice, video, and data traffic Different burstiness and flow durations Different QoS requirement

Network operations and networking equipment will be affected by the future traffic mix

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Flat over the next years Estimated by market studies forecasting [8]

Fixed landlines (PSTN), VoIP, mobile phone lines

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DPNM Lab.

Download rate during peak hours (6-10 p.m.) Studies investigating the Internet usage [10][11] Traffic pattern of more than twenty Internet exchange points

(IXPs) worldwide [12]

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Forecasting Market study from 2005 to 2009 in Western Europe [13] Predicting annual growth rate of roughly 55% with an

increase in the business segment and a growth decline in the consumer market

Summarize [12][14][15][16][17] to derive forecasting numbers

Using lower bound and upper bound to represent high uncertainty

Including P2P traffic to be data traffic

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IPTV Network ArchitectureIPTV Network Architecture VoD Content and User BehaviorVoD Content and User Behavior

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Super headend (SHE)

Video hub offices (VHOs) over the wavelength division multiplexed (WDM) national core Contain VoD servers

Video source offices (VSOs) also contain VoD servers that cache the more popular content

Central offices (COs)

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Packet routing and switching costs for VoD traffic

CEIF : the cost per bandwidth of Ethernet interfaces BVHO : the bandwidth of traffic to the VHO server cache HVHO : the number of packet routing hops this traffic

undergoes Btotal : the total quantity of VoD traffic Htotal : the number of packet hops that all of the VoD traffic

undergoes

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DPNM Lab.

The cost of the TDM switching and WDM transport is :

The cost for the VoD servers comes from the cost to store films on disk and the streaming interfaces from the video servers :

Cstorage is the cost per film for disk storage, and R is the number of films stored at the VSO.

NVSO is the number of VSO nodes, F is the total number of films offered, Cstream is the cost per VoD stream, and Nsessions is the number of simultaneous VoD sessions

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The authors believe that future VoD offerings will approach the number titles offered Today’s Netflix DVD mail-delivery service A catalog of about 60,000 films [19]

Applying Zipf distribution

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VoD Concurrency [% of Households] Percent Cached at VSO Relative Cost & Percent Cached at VSO Optimum Caching

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Using cost model to determine Ro, the optimum fraction of content stored at the VSOs.

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Cost curve for (a) a low

concurrency of 1% (b) a higher

concurrency of 10%

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Intuitively speaking, when the VoD usage becomes

high, the content should be delivered closer to the end

user

Intuitively speaking, when the VoD usage becomes

high, the content should be delivered closer to the end

user

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(a) the VoD traffic generated in the MAN

(b) VoD portion of total MAN traffic The voice and data

traffic are from the projections of Fig. 1-2 for 2010.

Error bars that come form upper and lower bounds of data traffic

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DPNM Lab.

The authors analyzed the bandwidth requirements in the MAN for IPTV systems.

They find that the bandwidth depends on where VoD content caching and video stream delivery is located.

The proposed cost model gives the optimal location for the content, and from that they determine that future networks could have a large percentage of real-time video traffic.

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