1

Towards Programmable Networks

Bikash Koley For Google Network Architecture ECOC Market Focus 2011

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

Google

Data Center

Google

Data Center

Google

Data Center

Google

Edge

Google

Edge

Google

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

Topology

8

Co

ntro

l

Co

mp

lex

ity

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

11

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

12