Title: IPTV%20Bandwidth%20Demands%20in%20Metropolitan%20Area%20Networks
1IPTV Bandwidth Demands in Metropolitan Area
Networks
- Jesse E. Simsarian and Marcus Duelk
- Bell Laboratories, Alcatel-Lucent, Holmdel, NJ,
jesses_at_alcatel-lucent.com - 15th IEEE Workshop on Local and Metropolitan Area
Networks, 2007 - Chen Bin Kuo (20077202)
- Young J. Won (20063292)
2Outline
- Introduction
- Data and Voice Traffic
- IPTV Network Architecture
- VoD Content and User Behavior
- Caching of Content
- Main Traffic
- Conclusion
3Introduction
- 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
4Introduction (contd.)
- Applying previous work on content delivery to a
realistic metropolitan area work (MAN) - Previous work unicast content delivery 12 ,
proxy server method 3, and multicast groups
45 - Considering a service provider is optimizing
content delivery - Assuming a small amount of buffering at the
clients set-top box - Delivery stream is viewed nearly in real time
- Do not consider VoD multicast 4
5Introduction (contd.)
- 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
6Data and Voice Traffic
- Voice Traffic
- Data Traffic
7Data and Voice Traffic
- 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
8Voice Traffic Estimation in the MAN
- Flat over the next years
- Estimated by market studies forecasting 8
- Fixed landlines (PSTN), VoIP, mobile phone lines
9Data Traffic Estimation in the MAN
- Download rate during peak hours (6-10 p.m.)
- Studies investigating the Internet usage 1011
- Traffic pattern of more than twenty Internet
exchange points (IXPs) worldwide 12
10Data Traffic Estimation in the MAN (contd.)
- 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 1214151617 to derive
forecasting numbers - Using lower bound and upper bound to represent
high uncertainty - Including P2P traffic to be data traffic
11- IPTV Network Architecture
- VoD Content and User Behavior
12IPTV Network Architecture
- 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)
13IPTV Network Architecture (contd.)
14Cost Model
- 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
15Cost Model (contd.)
- 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
16VoD Content and User Behavior
- The authors believe that future VoD offerings
will approach the number titles offered - Todays Netflix DVD mail-delivery service
- A catalog of about 60,000 films 19
- Applying Zipf distribution
17Caching of Content
- VoD Concurrency of Households
- Percent Cached at VSO
- Relative Cost Percent Cached at VSO
- Optimum Caching
18Caching of Content
19Caching of Content (contd.)
20Caching of Content (contd.)
- Using cost model to determine Ro, the optimum
fraction of content stored at the VSOs.
21Caching of Content (contd.)
- Cost curve for
- (a) a low concurrency of 1
- (b) a higher concurrency of 10
Intuitively speaking, when the VoD usage becomes
high, the content should be delivered closer to
the end user
22Optimum Caching
23MAN Traffic
24MAN Traffic
- (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
25Conclusion
- 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.
26Q AThanks for your attention!