IPTV%20Bandwidth%20Demands%20in%20Metropolitan%20Area%20Networks

1
IPTV 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)

2
Outline

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

3
Introduction

• 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

4
Introduction (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

5
Introduction (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

6
Data and Voice Traffic

1. Voice Traffic
2. Data Traffic

7
Data 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

8
Voice Traffic Estimation in the MAN

• Flat over the next years
• Estimated by market studies forecasting 8
• Fixed landlines (PSTN), VoIP, mobile phone lines

9
Data 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

10
Data 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

12
IPTV 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)

13
IPTV Network Architecture (contd.)
14
Cost 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

15
Cost 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

16
VoD 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

17
Caching of Content

• VoD Concurrency of Households
• Percent Cached at VSO
• Relative Cost Percent Cached at VSO
• Optimum Caching

18
Caching of Content
19
Caching of Content (contd.)
20
Caching of Content (contd.)

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

21
Caching 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
22
Optimum Caching
23
MAN Traffic
24
MAN 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

25
Conclusion

• 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.

26
Q AThanks for your attention!