towards programmable networks - ecoc exhibition focus 2011... · towards programmable networks...
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Scale Scale Scale
• User base • World population: 6.676 billion people (June'08, US Census est.)
• Internet Users: 1.463 billion (>20%) (June'08, Nielsen/ITU)
• Google Search: More than Billion Searches Every Day
• Geographical Distribution • Google services are worldwide: over 55 countries and 112 languages
• More than half of our searches come from outside the U.S.
• Data Growth • Web expands/changes: billions of new/modified pages every month
• Every few hours we crawl/refresh more than whole Library of Congress
• YouTube gains over 13 15 18 24 hours of video every minute, 1+billion views every day
• Latency Challenge • Speed of Light in glass: 2 x 10^8 m/s = 2,000 km / 10 ms
• “Blink of an eye response” = 100 ms
ATLAS 2010 Traffic report
Posted on Monday, October 25th, 2010 | Bookmark on del.icio.us
Google Sets New Internet Traffic Record
by Craig Labovitz
This month, Google broke an equally impressive Internet traffic record — gaining more than 1% of all Internet traffic share
since January. If Google were an ISP, as of this month it would rank as the second largest carrier on the planet.
Only one global tier1 provider still carries more traffic than Google (and this ISP also provides a large portion of Google’s
transit).
Google now represents an average 6.4% of all Internet traffic around the world. This number grows even larger (to as much
as 8-12%) if I include estimates of traffic offloaded by the increasingly common Google Global Cache (GGC) deployments
and error in our data due to the extremely high degree of Google edge peering with consumer networks. Keep in mind that
these numbers represent increased market share — Google is growing considerably faster than overall Internet volumes
which are already increasing 40-45% each year.
Warehouse Scale Computers
Servers • CPUs • DRAM • Disks
Racks • 40-80 servers • Ethernet switch
Clusters
Data-centers vs WSCs
Operating System
n
Transport Data Plane Optical
Transport Compute
HW
App App App
Operating System
1
Transport Data Plane Optical
Transport Compute
HW
App App App
Operating System
2
Transport Data Plane Optical
Transport Compute
HW
App App App
Network Network
Data-Center
Transport Data Plane Optical
Transport Compute
HW
Operating System/ File System
Transport Data Plane Optical
Transport Compute
HW
App App App
Transport Data Plane Optical
Transport Compute
HW
Network Network
App App App App App App
WSC
• Heterogeneous hardware/ system software/ apps
• Partitioned resources managed separately
• Inefficient Compute
• Homogeneous hardware/ system software
• Common pool of resources managed centrally
• Very Efficient Compute
A Warehouse-Scale-Computer(WSC) Network
Carrier/ISP Edge
Carrier/ISP Edge
Carrier/ISP Edge
Data Center
Data Center
Data Center
Edge
Edge
Edge
Layer Cake
• Service Layer – Massively Scalable, Highly Dynamic. Services Drive the Network. Application Layer Control Pushed Down Into Network.
• IP Layer – Standardized, Resilient and Universal Compute Interconnect and Service Delivery
• MPLS Layer – Forwarding, TE, Fast Restoral
• Optical Layer – Cost-effective simple, high-BW, point-to-point connectivity
Forwarding Plane(s)
•Ultimately, transporting flows end-to-end via:
– Layered Forwarding
– Layered statistical/discrete Multiplexing
– Layered rigid/flexible differential service classification
– Layered optimization
Fiber
(OTS/OMS) Wavelength OTN
/Ethernet
Labels
/Flows
Large inefficiency is built into this layered model
IP Control
Plane
Transport Data Plane Optical
Transport Router
EMS NMS App
Optical Control
Plane
Transport Data Plane Optical
Transport Optical
Transport
EMS NMS App
MPLS Control
Plane
Transport Data Plane Optical
Transport LSR
EMS NMS App
Towards Software Defined Networks
Layer-cake Network
Transport Data Plane Optical
Transport Router
Network Operating System
Transport Data Plane Optical
Transport Optical
Transport
App App App
Transport Data Plane Optical
Transport LSR
App App App App App App
Software Defined Network
• Looks Familiar?
• Heterogeneous control plane
• Heterogeneous network apps
• Same inefficiencies as yesterday’s data-centers
• Common network OS
• Common network apps
• Global view of network states
• Similar efficiency improvements as WSCs
Software Defined Optical Network
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Wavelength OTN /Ethernet
Labels /Flows
• Static channel spacing
• Static optical channel bandwidth
• Static channel bit-rate
Layer-cake Network
Wavelength OTN /Ethernet
Labels /Flows
• Dynamic grid spacing: Flex-grid ROADM
• Dynamic channel bandwidth: Super-carriers
• Dynamic channel bit-rate
Software Defined Network
What is Needed?
• Hardware Abstraction Layer (HAL)
• Common glue-layer for interfacing the NOS with the HAL: OpenFLow?
• Flex-grid ROADMs : minimum 12.5Ghz granularity
• Variable bit-rate optical transponders: multi-constellation modems
• Variable bandwidth channels: super-carriers/OFDM
• Variable bit-rate PHY layer support in the media-access-control (MAC) layer (e.g. variable bit-rate Tbit Ethernet)
• Global view of optical network-state and global optimization of bandwidth resource utilization through centralized compute
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