This document discusses next-generation optical access networks and moving toward providing 10 Gbps connectivity everywhere. It outlines several key points:
1) It discusses the business and architectural issues with current networks and the need for a paradigm shift toward more flexible, dynamically reconfigurable networks.
2) It proposes an ultimate optical network architecture using a common infrastructure for access, metro, and backbone networks to gain statistical multiplexing benefits across different traffic patterns and usage.
3) It introduces a quantitative analysis framework using an extended equivalent circuit rate (ECR) metric to define and measure a requirement of "10 Gbps everywhere" in a quantifiable way for different network architectures.
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Data Networks: Next-Generation Optical Access toward 10 Gb/s Everywhere
1. Data Networks:
Next-Generation Optical Access
toward 10 Gb/s Everywhere
Dr Kyeong Soo (Joseph) Kim (k.s.kim@swansea.ac.uk)
Multidisciplinary Nanotechnology Centre (MNC)
2.
3. Outline
• Business and Architectural Issues
• Paradigm Shift in Optical Networking
• Ultimate Optical Network Architecture
• Toward Next-Generation Optical Access
• ECR-Based Quantitative Analysis Framework
• Summary
5. Aim
• To identify promising routes forward in achieving the
goal of ―10 Gb/s everywhere‖, while making best use of
the existing knowledge in the literature and from earlier
projects.
– The solutions will show most promise of cost
effectiveness and power efficiency, and be future
proof (i.e., allowing bandwidth evolution and
infrastructure reuse).
7. Broadband Quality Score III
Univ. of Oxford and Universidad de
Oviedo,
sponsored by Cisco
September 2010
8. The State of the Internet by Akamai
(2nd Quarter, 2010 Report)
9. FTTH* vs. Cloud Computing**
SaaS*** User
SaaS Provider/
Cloud User
Cloud Provider
Web Apps
Utility computing
vs.
* NGOA Workshop, Mar. 2008.
** “Above the clouds”, UC Berkeley.
*** SaaS: Software as a Service
10. FTTH Business Perspective*
Layer Economic
Character
Life Cycle Cost per
Subscriber
Service Layer Low CapEx,
average to high
OpEx
1 to x years ?
Active Layer Average CapEx,
low OpEx
5 to 10 years €300~500
Passive Layer High CapEx, very
(very) low OpEx
25 to 50 years €500~700
•NGOA Workshop, Mar. 2008.
11. Cloud Computing: New Aspects in Hardware*
• The illusion of infinite computing resources available on
demand
– Through the construction of large-scale, commodity-computer
datacenters at low cost locations, and virtualization technique
• The elimination of up-front commitment by Cloud users
– Companies can start small and increase gradually
• The ability to pay for use of computing resources on a
short-term basis as needed
* “Above the clouds”, UC Berkeley.
12. Cloud Computing: Economic Benefits*
• Elasticity
– Ability to add or remove
resources at a fine grain
and with a small lead time
• Transference of risks of
– Overprovisioning
(underutilization)
– Underprovisioning
(saturation)
* “Above the clouds”, UC Berkeley.
Max. (=peak)
Min.
Avg.
Time
Demand
13. Cloud Computing: A New Killer Application for
Next Generation Optical Internet Access?
• Data transfer bottlenecks (to and from Clouds)
– Example: Move 10 TB from UC Berkeley to Amazon in
Seattle*
• WAN link of 20 Mb/s: 4 Msec ≈ 46 days
• Overnight shipping (FedEx): < 1 day (≈ 1.5 Gb/s)
• 10 Gb/s link: ≈ 2 hours
» Even better if we could use more than 10 Gb/s
for a short period!
* “Above the clouds”, UC Berkeley.
15. Current Network Limitations
• Bandwidth-hungry services (e.g., VoD, IPTV):
– Increase the amount of network infrastructure
– Increase the network energy consumption
– Increase the data-driven network crashes
• Due to:
– Unbalance in capacity between core and access
– Mismatch between service/usage models and network
infrastructure
– Large number of power-hungry and error-prone electrical
components/systems
16. Paradigm Shift in Optical Networking
• Changes in network architectures
– Performance Energy efficiency driven
– Static Dynamically reconfigurable network
– Dedicated Shared resources
– Separate & complicated Integrated &
simplified management layers/interfaces
– Unbalanced Balanced bandwidth link utilization
20. Enabling Technologies
• Common denominator in technologies enabling
flexible, dynamically-reconfigurable optical networks
– New multiple access technologies
• e.g., Hybrid TDM/WDM, OFDMA with POLMUX
– Tunable transmitters (lasers) and receivers (filters)
– Burst-mode communications
• The paradigm shift pushes these technologies
toward the edge of the networks!
21. Ultimate Optical Network Architecture - 1
• A common network
architecture/infrastructure
for access/metro/backbone
• To enjoy the benefits of
Economy of Scale* by
maximizing statistical
multiplexing gain over
– Traffic burstiness
– Different usage patterns
• Challenge: How to
integrate them all?
Backbone/CoreBackbone/CoreMAN
Access
Access
Residential
Users
Business
Users
Access/MAN/Backbone
Residential
Users
Business
Users
* Factors of 5 to 7 decrease in cost (“Above the clouds”, UC Berkeley)
22. Ultimate Optical Network Architecture - 2
• Network resource as
utility
• Cut the (static) link
between fibre
infrastructure and pool of
network resources (e.g.,
transceivers)
• Challenge: Everything
(both up- and downstream)
in burst-mode
communications
Fibre Infrastructure
(Access/MAN) …
Transceivers
X
24. Ultimate Optical Network Architecture:
Example
SUCCESS-HPON – Hybrid TDM/WDM-PONs
(2003-2005)
Central
Office
RN
RN
RN
RN
’
1, 2
1
2
21
22 23
’
1
’
3, 4, …
1, 2
3, 4, …
3
’
3
3
31
32
33
TDM-PON ONU
RN TDM-PON RN
WDM-PON ONU
RN WDM-PON RN
Central
Office
RN
RN
RN
RN
’
1, 2
1
2
21
22 23
’
1
’
3, 4, …
1, 2
3, 4, …
3
’
3
3
31
32
33
TDM-PON ONU
RN TDM-PON RN
WDM-PON ONU
RN WDM-PON RN
Protection & restoration is
possible by using different s
on east- and west- bound.
25. Benefits of Flexible Architecture
R
Tunable
TX 1
Power
Splitter
WDM
DEMUX
ONU 1
ONU 16
...
Start small and grow gradually
26. Benefits of Flexible Architecture
R
R
Tunable
TX 1
Tunable
TX 2
Power
Splitter
WDM
DEMUX
ONU 1
ONU 32
...
Start small and grow gradually
27. Benefits of Flexible Architecture
R
R
Tunable
TX 1
Tunable
TX 2
Power
Splitter
WDM
DEMUX
ONU 1
ONU 48
...
R
Tunable
TX 3
Start small and grow gradually
28. Benefits of Flexible Architecture
R
R
Tunable
TX 1
Tunable
TX 2
Power
Splitter
WDM
DEMUX
ONU 1
ONU 64
...
R
Tunable
TX 3
R
Tunable
TX 4
Start small and grow gradually
29. Benefits of Flexible Architecture
R
R
Tunable
TX 1
Tunable
TX 2
Power
Splitter
WDM
DEMUX
ONU 1
ONU 64
...
R
Tunable
TX 3
R
Tunable
TX 4
Flexibility and power efficiency
Usage = 50%
(Compared to Peak)
Turn off TX3 & TX4 to save energy
30. Benefits of Flexible Architecture
R
R
Tunable
TX 1
Tunable
TX 2
Power
Splitter
WDM
DEMUX
ONU 1
ONU 64
...
R
Tunable
TX 3
R
Tunable
TX 4
Redundancy and hot-swap capability
TX4 failed
The system is still running (with
slightly degraded performance)
32. Evolution of Optical Access
OLT
ONU
ONU
ONU
OLT
ONU
ONU
TDM-PON
OLT
ONU
ONU
ONU
ONU
OLT
ONU
ONU
ONU
? LR-PON
WDM-PON
Hybrid PON
33. Geneva, 19-20 June 2008
Evolution scenario
Now ~2010 ~2015
Power splitter deployed for Giga PON
(no replacement / no addition)
Splitter for NGA2
(power splitter or
something new)
G-PON
GE-PON
WDM option to
enable to overlay
multiple G/XGPONs
Co-existence
“Co-existence”
arrows mean to
allow gradual
migration in the
same ODN.
NG-PON2
E.g. Higher-rate TDM
DWDM
Elect. CDM
OFDM,Etc.
Equipment
be common
as much as
possible
NG-PON1 incl.
long-reach option
Capacity
XG-PON
(Up: 2.5G to 10G,
Down: 10G)
Co-existence
Component R&D to enable NG-PON2
A Suggested Time Line from ITU-T/IEEE*
* J. Kani and R. Davey , “Requirements for Next Generation PON,”
Joint ITU-T/IEEE Workshop on NGOA, Jun. 2008.
34. Areas of Improvement
• Reach
– Through amplification
• Bandwidth per subscriber
– Higher transmission rate in TDM-PON
– Introduction of WDM
• User base
– Serving both residential and business users
through common infrastructure
• Stronger protection capability for business users
35. Candidates for NGOA
• LR-PON
– 10 Gb/s over 100km with up to 1000:1 split ratios*
• WDM-PON
– Use of array of transceivers
– Lack of BW sharing
– Inventory management of ONUs with different s
– Need of colorless or sourceless ONUs
• Hybrid TDM/WDM-PON
– Use of fast tuneable lasers (and receivers)
– Flexible architecture, but complex MAC/scheduling
– How-swapping capability of tuneable components
* MIT CIPS Optical Broadband Working Group
36. Challenges
• Power Efficiency
– Number of high-powered transceivers and optical amplifiers in use
• Maintenance
– For active components and thermal optical devices in the field
• Backward compatibility
– For current-generation TDM-PONs
• Scalability
– Start small and grow gradually
• Integration with other services
– Wireless/Video overlay
39. Requirements for 10-Gb/s Optical Access
• ―10 Gbit/s everywhere‖ is taken to mean that any customer premises can
cost-effectively access useful end-to-end symmetrical throughputs of
10Gb/s data on demand (i.e., whenever they want it but it need not
necessarily always be there).‖ [Excerpt from TSB project requirements]
– Major focus on residential and SME customers.
– 10 Gb/s line rate in the access is a necessary but not sufficient condition.
– Some degree of contention assumed at various points in the network
• What is missing here?
– Description/definition which is
• Specific (e.g., What is ―useful‖?)
• Practical & implementable (e.g., any shared architecture can achieve this?)
• Measurable (during the operation in the field)
40. What Does “10 Gb/s” Means?
• We need a quantifiable and
measurable definition of ―10 Gb/s‖
at the user side for
– Comparative study of candidate
architectures
– Actual implementations
• Our proposal is based on the
extension of the equivalent circuit
rate (ECR)*.
– For general services & applications
in addition to web-browsing and
interactive data
– Taking into account access/metro
part only
* N.K. Shankaranarayanan, Z. Jiang, and P. Mishra,
“User-perceived performance of web-browsing and
interactive data in HFC cable access networks,” Proc. Of
ICC, pp. 1264-1268, Jun. 2001.
Server
User
User
Candidate architecture
Server User
User
Y
Z = α*min(X, Y) (α < 1)
The same
perceived
performance
X
41. Implications on Metro/Access* Architectures - 1
• If we mean by ―10 Gb/s‖ the (extended) ECR of
the network architecture (i.e., Z), we can derive
the following conclusions:
– Point-to-point (including static WDM-PONs)
architectures with a UNI (i.e., Y) of 10 Gb/s can meet
the requirement.
• As far as the NNI (i.e., X) is not a bottleneck.
• But there is no statistical multiplexing gain (i.e., sharing of
resources) in this architecture.
* Not end-to-end.
42. Implications on Metro/Access Architectures - 2
– Shared architectures with a UNI of 10 Gb/s may not meet this
requirement (i.e., ECR < 10 Gb/s), irrespective of NNI.
• Need to increase either line rate (for TDM-PON & hybrid
TDM/WDM-PON) or number of WDM channels (for hybrid
TDM/WDM-PON) at the UNI.
• Note that the ECR is a function of the architecture, the number
of users, and the nature of services/applications.
43. ECR-Based Quantitative Analysis Framework –
Rationale
• To take into account the interactive nature of actual traffic (e.g.,
TCP flow control) and the performances perceived by end-users
(e.g., delay in web browsing) in quantification of the statistical
multiplexing gain.
• To capture the interaction of many traffic flows through TCP and a
candidate network architecture.
– Simulation models based on OMNeT++ and INET Framework have
been implemented, which provide models for applications as well as
a complete TCP/IP protocol stack.
44. Calculating ECR
•DW,R: Web page delay from reference architecture
•DW,C: Web page delay from candidate architecture
Start
i=0
R=R’=Ri
Two-sample hypothesis testing with
•H0: E[DW,R] = E[DW,C]
•H1: E[DW,R] < E[DW,C]
Reject
H0?
Yes
i=i+1
R’=R
R=Ri
Two-sample hypothesis-testing with
•H0: E[DW,R] = E[DW,C]
•H1: E[DW,R] E[DW,C]
No
Reject
H0?
ECR=
(R + R’)/2
Yes
ECR=R
No
End
47. Simulation Setup: System Parameters
• N: Number of ONUs (subscribers)
• n: Number of hosts (users) per ONU
• RD: Rate of distribution fibre
• RF: Rate of feeder fibre
• RB: Rate of backbone network (>> N × RD)
• RTT: End-to-end round trip time
48. System Model - ECR Reference
• N = 16
• n = 1, 2, …
• RU = RD = RF = 10 Gbit/s
• RB = 1 Tbit/s (future standard or MUX of 100 Gbit/s links)
• RTT = 10 ms (including 600 µs RTT in 60-km PON)
App.
Server
ONU
1
ONU
N
…
RD=RF
Host 1
Host n
…
Host 1
Host n
…
RTT
RB
OLT
RU
49. System Model – Hybrid PON
• N = 16
• n = 1, 2, …
• RU = RD = RF = 10 Gbit/s
• TX = RX = 1, 2, …
• RB = 1 Tbit/s
• RTT = 10 ms
RF App.
Server
ONU
1
ONU
N
…
RD
RD
Host 1
Host n
…
Host 1
Host n
…
RTT
RB
OLT
RU
TX, RX
52. Overview of Host (User) Node - 1
HTTP 1
TCP
UDP
Network
and
Lower
Layers
HTTP nh
…
FTP 1
FTP nf
…
Video 1
Video nv
…
UNI
53. Overview of Host (User) Node - 2
• nh = nv = 1
– Assume that a user can watch only one video channel and
interact with only one web session simultaneously at any given
time.
• As far as user perceived (interactive) performance is concerned.
• nf should be kept large to load the high-speed access link.
– FTP is usually background process.
• This could be HTTP sessions just downloading files.
– Suggest 10 as a starting point.
54. Observations & Comments
• For study of network architectures/protocols, the
frame/packet-level traffic modelling is not very useful.
– e.g., Packet inter-arrival statistics highly depend on network
architectures/protocols.
• We will focus on application level traffic modelling, i.e.,
above transport layer (TCP/UDP).
– Statistics on sources (e.g., file size for FTP and frame size for
video) and user behaviour are critical.
– It is, however, extremely difficult to find such data!
55. HTTP Traffic Model - 1
• A behavioural model for user(s) web browsing based on [2] with following
simplification:
– No caching and pipelining
– Adapted for traffic generation at the client side
Server
Client
Request for
HTTP object
Request
for embedded
object 1
Response
Parsing Time Reading Time
…
Request
for embedded
object 2
Response to the last
embedded object
Request
for HTTP
object
Web page delay (= session delay*)
* Include connection (i.e., socket) set-up time as well (which is not shown in the figure).
56. HTTP Traffic Model -2
Parameters / Measurements Best Fit (Parameters)
HTML Object Size [Byte] /
Mean=11872, SD=38036, Max=2 M
Truncated lognormal (=7.90272,
=1.7643, max=2 M)
Mean=12538.25, SD=45232.98
Embedded Object Size [Byte] /
Mean =12460, SD=116050, Max=6 M
Truncated lognormal (=7.51384,
=2.17454, max=6 M)
Mean=18364.43, SD=105251.3
Number of Embedded Objects /
Mean=5.07, Max=300
Gamma (=0.141385, =40.3257)
Mean=5.70, SD=15.16
Parsing Time [sec] /
Mean=3.12, SD=14.21, Max=300
Truncated lognormal (=-1.24892,
=2.08427, max=300)
Mean=2.252969, SD=9.68527
Reading Time [sec] /
Mean=39.70, SD=324.92, Max=10000
Lognormal (=-0.495204, =2.7731)
Mean=28.50, SD=1332.285
Request Size [Byte] /
Mean=318.59, SD=179.46
Uniform (a=0, b=700)
Mean=350, SD=202.07
57. Streaming Video Traffic Model - 1
• HDTV quality, realistic, high bit-rate video traffic models are
needed for NGOA
– Use H.264/AVC video traces
– ―Terminator 2‖ VBR clip from ASU Video Trace Library
• Duration: ~10 min
• Encoder: H.264 FRExt
• Frame Size: HD 1280x720p
• GoP Size: 12
• No. B Frames: 2
• Quantizer: 10
• Mean frame bit rate: 28.6 Mbit/s
» ~334 streams needed to fill 10 Gbit/s line with the following assumption.
58. Streaming Video Traffic Model - 2
• Interface with OMNeT++/INET framework
– Through ―UDPVideoStream{Svr,Cli}WithTrace‖ modules:
• UDP server can handle multiple client requests simultaneously
• Random starting phase for each request
• Wrap around to generate infinite streams
• UDP client records the following performance metrics:
» Packet end-to-end delay (vector)
» Packet loss rate
» Frame loss rate
» Decodable frame rate (perceived quality metric)
59. FTP Traffic Model - 1
• A simple model for user(s) file downloading based on [3]:
– The model is for a data transfer connection only.
– Multiplexed (nf = 10) to emulate future FTP/data services at 10 Gbit/s rate
– Adapted for traffic generation at the client side
Server
Client
Request for
a file to download
Reading Time
Response to the last
embedded object
Request for
a file to download
File download delay
(= session delay)
60. FTP Traffic Model -2
Parameters Probability Distribution Function
(PDF)
File Size [Byte] /
Mean=2 M, SD=0.722 M, Max=5 M
Truncated lognormal (=14.45,
=0.35, max=5 M)
Mean=1995616(~2 M),
SD=700089.8(~ 0.70M)
Reading Time [sec] /
Mean=180
Exponential (=0.006)
Mean=166.667, SD=166.667
Request Size [Byte] /
Mean=318.59, SD=179.46
Uniform (a=0, b=700)
Mean=350, SD=202.07
61. Simulation Environment
OMNeT++ with
INET framework
Streamline Linux Cluster
• 22 computing nodes (each with 8 cores and 8GB memory)
• Total 176 cores and 176 GB memory
67. Discussions - 1
• Dedicated architectures with 10-Gb/s line rate — including
static WDM-PON — can provide 10-Gb/s ECR (by
definition).
– As far as there is no contention in the network side.
– But, we cannot enjoy any statistical multiplexing gain
(i.e., sharing of resources) other than some fibre
infrastructure in case of WDM-PON.
68. Discussions - 2
• Hybrid TDM/WDM-PON with 10-Gb/s line rate can also provide
10-Gb/s ECR with multiple transceivers whose number
depends on traffic load.
– It is remarkable that hybrid PON with just one transceiver
can achieve 10-Gb/s ECR until n reaches 5.
• When n=5, streaming video traffic alone pushes about
150-Mb/s stream into ONU and 2.4-Gb/s multiplexed
stream into OLT (out of 16 ONUs).
– An ideal shared architecture would be that of large split
ratio with multiple wavelength channels.
• i.e., SuperPON + hybrid TDM/WDM-PON
69. Summary
• Changing business environment and demands are driving
forces behind the paradigm shift in optical networking toward
– Flexible, dynamically-reconfigurable network to better utilize network
resources
– Passive/semi-passive network to maximise energy efficiency
– A common network infrastructure for access/metro/backbone
• We have been working on the following tasks to realize 10-
Gb/s NGOA solutions:
– Investigate candidate architectures in terms of cost, power efficiency,
maintenance, scalability, and extensibility.
– Propose ECR-based comparative analysis framework and
demonstrate benefits of shared architecture (e.g., hybrid PON) based
on it.
70. References
1. N.K. Shankaranarayanan, Z. Jiang, and P. Mishra, ―User-
perceived performance of web-browsing and interactive
data in HFC cable access networks,‖ Proc. Of ICC, pp.
1264-1268, Jun. 2001.
2. J. J. Lee and M. Gupta, ―A new traffic model for current
user web browsing behavior,‖ Research@Intel, 2007
[Available online].
3. cdma2000 Evaluation Methodology, 3GPP2 C.R1002-B,
3GPP2 Std., Rev. B, Dec. 2009 [Available online].
70
71. Questions?
Thank you for your time!
For more information on today’s
presentation, please visit
http://iat-hnrl.swan.ac.uk/~kks/