NREN strategies for Data-Intensive Science in a Carbon Constrained World

NREN strategies for Data-‐Intensive Science in a Carbon Constrained

World

Bill St. Arnaud

[email protected]

Unless otherwise noted all material in this slide deck may be reproduced, modified or distributed without prior permission of the author

Theme of this talk •  We have already lost the baIle to save the planet from extreme

climate change. Rather than focusing on reducing energy consumpKon, (MiKgaKon) we now need to focus on surviving climate change (AdaptaKon)

•  Explosion of data and energy consumpKon by computers and networks is contribuKng to energy demand and CO2 emissions

•  But big data and science will be criKcal as move to focus on adapKng to climate change

•  How can Internet and IT help us build NRENs and support science

and educaKon that can adapt to global warming?

Changing NREN networking environment

•  Global Virtual Research CommuniKes

•  Increasing co-‐operaKon between public and private researchers

•  Rapidly changing users demands

•  Increasing potenKal of commercial ICT-‐service providers

•  EducaKon: any Kme, any place, any device

•  CiKzen Science and M2M communicaKons and sensors

•  The disappearing campus IT & diminishing experKse in ICT centres of connected insKtuKons

Although there is less news coverage global warming has not disappeared

Half of US experienced record droughts or deluges in 2011

2010 warmest year ever – we are only at the start of the curve of the hockey s7ck. The worst is yet to come

Blame it on Canada How warming in the ArcKc affects weather in Louisiana

•  Warming ArcKc slowing down jet stream •  Basic Thermodynamics -‐ polar temperatures

drive the jet stream, –  There’s been a 20 percent drop in the zonal

wind speeds. •  As get stream slows down, it leads to those

bigger kinks in the jet stream. –  That amplificaKon is associated with

persistent weather paIerns that lead to “extremes” like drought, flooding and heat waves.

•  Those slow-‐moving, persistent waves of weather energy may have played a role in the big snows that hammered parts of the West last winter, as well as some of the extreme winter weather that hit South West US and Europe

•  hIp://summitcountyvoice.com/2012/01/14/global-‐warming-‐revenge-‐of-‐the-‐atmosphere/

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Climate Forecasts

MIT

•  MIT report predicts median temperature forecast of 5.2°C –  11°C increase in Northern Canada

& Europe –  hIp://globalchange.mit.edu/pubs/

abstract.php?publicaKon_id=990

•  Last Ice age average global temperature was 5-‐6°C cooler than today –  Most of Canada & Europe was

under 2-‐3 km ice

•  Nearly 90 per cent of new scienKfic findings reveal global climate disrupKon to be worse, and progressing more rapidly, than expected. •  hIp://www.skepKcalscience.com/pics/

Freudenburg_2010_ASC.pdf

Future Droughts •  Palmer Drought Severity Index, or PDSI.

•  The most severe drought in recent history, in the Sahel region of western Africa in the 1970s, had a PDSI of -‐3 or -‐4.

•  By 2030 Western USA could see -‐4 to -‐6. Drought in Texas clearly caused by global warming: hIp://goo.gl/QjHRS

•  By 2100 some parts of the U.S. and LaKn America could see -‐8 to -‐10 PDSI, while Mediterranean areas could see drought in the -‐15 or -‐20 range.

hIp://www.msnbc.msn.com/id/39741525/ns/

us_news-‐environment/

DramaKc changes in precipitaKon

•  Every conKnent has suffered record rainfalls •  Rains submerged one-‐fioh of Pakistan, a

thousand-‐year deluge swamped Nashville and storms just north of Rio caused the deadliest landslides Brazil has ever seen.

•  Observed increase in precipitaKon in the last few decades has been due in large part to a disproporKonate increase in heavy and extreme precipitaKon rates which are exceeding predicKons made in models

New Challenge: Climate AdaptaKon

•  Obama’s NaKonal Science Advisor John Holdren “MiKgaKon alone won’t work, because the climate is already changing, we’re already experiencing impacts….A miKgaKon only strategy would be insanity,”

•  Equal emphasis given to adaptaKon – avoiding the unmanageable, and adaptaKon – managing the unavoidable.”

•  Obama’s Climate AdaptaKon ExecuKve Order

–  hIp://www.stumbleupon.com/su/1tU8go/www.good.is/post/obama-‐s-‐secret-‐climate-‐adaptaKon-‐plan/

Climate Change Impact on Internet and NRENs

•  UK Government study Climate Change could ruin the Internet –  hIp://www.grist.org/list/2011-‐05-‐09-‐climate-‐change-‐could-‐ruin-‐the-‐internet

•  California aims to have 30% renewable power

–  Impact on reliability of power systems

•  Last year Nuclear power plants in France were forced to shut down because cooling water was too warm

•  Germany is commiIed to shuvng down all of its nuclear plants •  Droughts will restrict producKon of hydro-‐electric power

•  Energy shortages and disrupKons are predicted to increase in the coming years

Impact on ICT sector

www.smart2020.org

According to IEA ICT will represent 40% of all energy consump7on by 2030

ICT represent 8% of global electricity consumpKon Future Broadband-‐ Internet alone is expected to consume 5% of all electricity hIp://www.ee.unimelb.edu.au/people/rst/talks/files/Tucker_Green_Plenary.pdf

R&E biggest consumer!!

Australian Computer Society Study hIp://www.acs.org.au/aIachments/ICFACSV4100412.pdf

Per employee Per sector

The ICT energy consumpKon in higher-‐ ed

•  Campus compuKng 20-‐40% electrical energy consumpKon on most campuses –  Studies in UK and The Netherlands –  hIp://goo.gl/k9Kib

•  Closet clusters represent up to 15% of electrical consumpKon

–  hIp://isis.sauder.ubc.ca/research/clean-‐technology-‐and-‐energy/green-‐it/

•  Campus data center alone represents 8-‐20% of electrical consumpKon –  hIp://www.iisd.org/publicaKons/pub.aspx?pno=1341

•  IISD study demonstrated that moving Canadian research to cloud would

pay for itself in energy savings and CO2 reducKon –  hIp://www.iisd.org/publicaKons/pub.aspx?pno=1341

The real cost of campus compuKng

•  Land -‐ 2% •  Core and shell costs – 9% •  Architectural – 7% •  Mechanical/Electrical – 82%

–  16% increase/year since 2004 Source: ChrisKan Belady

Belady, C., “In the Data Center, Power and Cooling Costs More than IT Equipment it Supports”, Electronics Cooling Magazine (February 2007)

The Data Deluge

Genomic sequencing output x2 every 9 month

Climate model intercomparison project (CMIP) of the IPCC

2004: 36 TB

2012: 2,300 TB

1330 molec. bio databases Nucleic Acids Research (96 in Jan 2001)

MACHO et al.: 1 TB Palomar: 3 TB 2MASS: 10 TB GALEX: 30 TB Sloan: 40 TB Pan-‐STARRS:

40,000 TB

Source: Ian Foster, UoChicago

Big science has achieved big successes

LIGO: 1 PB data in last science run, distributed worldwide

ESG: 1.2 PB climate data delivered to 23,000 users; 600+ pubs

OSG: 1.4M CPU-‐hours/day, >90 sites, >3000 users, >260 pubs in 2010

Robust producKon soluKons SubstanKal teams and expense Sustained, mulK-‐year effort ApplicaKon-‐specific soluKons, built on common technology


But small science is struggling

More data, more complex data Ad-‐hoc soluKons Inadequate sooware, hardware Data plan mandates


Growth in sensor networks and CiKzen Science

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Real Time Health Monitoring

Glacier Tracking

Smart Trash

THE CHALLENGE We need soluKons to address climate change, data deluge, needs of scienKsts, global collaboraKon, the evolving network of any Kme, any place, any device and yet addresses the challenge of disappearing IT on campus while sKll providing a leadership role in next generaKon Internet and broadband, and find ways to pay for it all in an era of severe fiscal constraint.

THE SOLUTION

1.  Brokered Green Clouds and off site campus IT 2.  Sooware Defined Networks (OpenFlow) 3.  NREN naKonal wireless network 4.  Global Interconnected Dynamic OpKcal Networks 5.  eScience Pla|orms with next gen IdM 6.  Community anchor IXPs with CDN and M2M hosKng 7.  New billion dollar revolving green energy funds at many

universiKes

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1. Brokered Green Clouds and off site CAMPUS IT

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UniversiKes moving to eliminate IT departments

•  Already many primary funcKons of IT department are being outsourced to the cloud –  E-‐mail, web, DNS, research compuKng, etc –  University of Western Australia has outsourced virtually all campus servers to

an external private cloud

•  Even rouKng, network and firewall funcKons being outsourced to NREN –  AARnet, SUnet and other NRENs offering border gateway rouKng services with

collapsed IP backbones –  Sooware Defined Networks makes it easy to configure outsourced LAN –  Network faciliKes can be located

•  Increasingly most traffic is in/out of campus, instead of within –  Social networking, P2P, Clouds, Kuali, Blackboard –  Future of Campus IT – high speed opKcal network connected to WiFi/5G hot

spots with tablets –  No servers, no LAN

MIT to build zero carbon data center in Holyoke MA

•  The data center will be managed and funded by the four main partners in the facility: the MassachuseIs InsKtute of Technology, Cisco Systems, the University of MassachuseIs and EMC.

•  It will be a high-‐performance compuKng environment that will help expand the research and development capabiliKes of the companies and schools in Holyoke –  hIp://www.greenercompuKng.com/news/2009/06/11/

cisco-‐emc-‐team-‐mit-‐launch-‐100m-‐green-‐data-‐center

NREN Brokered Cloud for IT departments and Researchers

•  Internet 2 Net + –  Provisioning of mulK vendor cloud services leveraging the Internet2

Network and InCommon Federated AuthenKcaKon –  Interoperable marketplace for services where individual insKtuKons

might procure services from a wide range of cloud services providers.

•  HEFCE and JISC to Deliver Cloud-‐Based Services for UK Research

–  Besides providing brokered cloud services they are also providing cloud “soluKons” for IT departments and researchers

–  hIp://www.hpcinthecloud.com/hpccloud/2011-‐06-‐27/hefce_and_jisc_to_deliver_cloud-‐based_services_for_uk_research.html?utm_medium=twiIer&utm_source=twiIerfeed

•  SURFnet: Community Cloud Models and the Role of the R&E network as a

broker for cloud services –  hIp://www.slideshare.net/haroldteunissen/community-‐clouds-‐shared-‐infrastructure-‐as-‐a-‐service

2. So\ware Defined networks

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GreenStar Network World’s First Zero Carbon Cloud/Internet

OpenFlow Follow the wind/Follow the sun

Cloud Manager

Host Resource

Cloud Manager

Network Manager

VM

Mantychore2

Host Resource

Canadian GSN Domain

European GSN Domain

Dynamically Configure IP Tunnel

•  Shudown VM •  Copy Image •  Update VM Context

•  Start VM

Export VM

VM VM

Internet

NoKfy EU Cloud Manager

Cloud Proxy Host Cloud Proxy

Lightpath

OpKcal switch OpKcal switch

Shared storage

Shared storage

Host

OpenFlow-‐based cloud

Open Virtual Switch (OVS)

Host

eth0 eth1

Ethernet Switch

Open Virtual Switch (OVS)

Host

eth0 eth1 Open Virtual Switch (OVS)

Host

VM VM

eth0 eth1 Open Virtual Switch (OVS)

Host

VM

eth0 eth1

VM

OpenFlow Control plane OpenFlow Data plane

OF Controller

OpenFlow Network B

OVS

eth0 eth1

Internet

eth0 eth1

OVS

VM VM VM VM

OpenFlow Network A

Green Clouds InternaKonal •  GreenLight explores how researchers can take advantage of data centers linked by

high-‐speed networking in an era of carbon-‐thrioy compuKng •  Recent studies migraKng virtual machines to green energy sites indicate that 100

Gb/s networks are far superior to 10 Gb/s to make this transparent. •  SURFnet 7 lightpath connecKon to GreenQCloud in Iceland

SURFconecxt control of lightpath to GreenQCloud in Iceland

Future Global Network of Green Clouds interconnected by GLIF

Science Cloud CommunicaKon Services Network

•  Enterprise clouds use commodity internet; computaKonal clouds for data-‐intensive science require dynamic cloud provisioning integrated with dynamic high performance.

•  TransCloud: example of dynamic networking & dynamic cloud provisioning

Example of working in the TransCloud [1] Build trans-‐con7nental applica7ons spanning clouds: •  Distributed query applica7on based on Hadoop/Pig •  Store archived Network trace data using HDFS •  Query data using Pig over Hadoop clusters [2] Perform distributed query on TransCloud, which currently spans the following sites: •  HP OpenCirrus •  Northwestern OpenCloud •  UC San Diego •  Kaiserslautern

Source: Maxine Brown

3.0 NREN Na7onal Wireless Network

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Building a NREN wireless network •  Vision: to allow students, researchers and employees to collaborate,

research, learn anyKme and anywhere they seem fit!

•  Also Internet of Things – Machine to Machine communicaKons •  ExisKng 3G and 4G networks cannot handle data load

–  Roaming gateways prevent global seamless access –  Voice centric architectures

•  New mobile networks seamlessly integrate with WiFi on campus

–  New Wifi 2.0 standards 802.11u allow for data handoff from 3G networks

–  Eduroam can be the global authorizaKon tool –  OpenFlow can be used to architect integrated soluKons from wireless

node across opKcal network

Impact of NREN wireless networks

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•  The phone is a also a sensor pla|orm •  Processing is done in real Kme in the cloud

–  Allowing processing that can’t be done on the device –  Big data analysis

•  New campus or hot spot centric architectures integraKng LTE and Wifi –  See SURFnet pilot

hIp://www.surfnet.nl/en/nieuws/Pages/BackgroundarKcle.aspx

•  WiFi nodes can be powered by renewable sources such as roof top solar panel over 400Hz power systems or ethernet power

The Regulatory Challenge •  Today’s SIM-‐card locks user to the network •  If NREN becomes a MVNO with own SIM-‐cards, users could

roam seamlessly around the globe •  Only public service providers have access to IMSI-‐numbers for

SIM-‐cards

•  One opKon is to lobby regulators to give R&E networks access to IMSI-‐numbers

4. Global Interconnected Dynamic Op7cal Networks

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GLIF

37

GOLE

e-‐Research Scenario

38 Source: SURFnet

Importance of GOLEs •  Increasingly more research and educaKon is internaKonal collaboraKon

–  Cornell-‐ Technion announcement –  US overseas university campuses in UK and elsewhere –  GOLES enable direct peering of regional networks or even insKtuKons

•  Many researchers need access to commercial clouds and data specialists –  AUP issues ooen prevent NRENs from directly connecKng up these insKtuKons –  Genomics and bio-‐informaKcs processing and climate modeling

•  Many commercial research insKtuKons need access to lightpaths –  GOLES provide neutral access points for interconnect to AUP free lightpaths

•  Enables new services –  Sooware Defined Network using Switched lambdas

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5. eScience Plaiorms with next gen IdM

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Towards “research IT as a service” Scientific data management as a service

GO-CatalogGO-Compute

GO-Store GO-Galaxy

GO-Team

GO-TransferGO-Collaborate

GO-User

Source: Ian Foster, UoChicago 41

SaaS services in acKon: The XSEDE vision

Globus Online: Hosted persistent services

User Team Compute

InCommon

XSEDE service providerCommercial

provider

Catalog ...

Data provider

Open Science

Grid

Transfer

...

Academic institution

2

= Standard interface

XUAS

42

Virtual OrganisaKons

NBIC

Group

Netherlands BioInformatics Centre (NBIC)

Apps.NB

IC.nl

Supporting Services •  SURFfederatie •  SURFteams •  OpenSocial

M

y Ex

perim

ent

Pu

bMed

Grid

res.

Publ

ishe

r

N=6 N=10 N=30 Guests N=20

N=66

Virtual IdP Network

Services Storage Services

Compute

Services

Network Broker

Storage Broker

Compute Broker

Instrument

Services

Instrument Broker

CollaboraKon Infrastructure (SURFconext)

Generic Broker

AAI provisioning

groups

A6rib.

mgmt

…

Source: SURFnet

6. eScience and Big Data for CiKzen Science and Community

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Extending science and educaKon to the community

•  Community anchor Internet Exchange Points help clear the boIleneck of content peering –  Co-‐hosKng of CDN caching boxes –  Managed by NREN –  Examples include KAREN (New Zealand), BCnet and UNINETT (Norway)

•  Minimize tromboning of R&E traffic to homes and schools •  Can support extension of Eduroam to community WiFi spots and/or

community last mile networks •  Allows for M2M traffic and anywhere, anyKme traffic to propagate through

the community

45

Community IXP managed by NREN

7. How to pay for it all

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$1 billion funding program •  Green revolving funds are either part of a university endowment program or publicly traded

enKKes. –  hIp://www.sustainablebusiness.com/index.cfm/go/news.display/id/23028

•  They make investments in energy efficiency and GHG reducKon iniKaKves. Payback typically

32% •  ICT can represent up to 40% of the electrical energy consumpKon at university and growing

•  The obvious low hanging fruit is to move, as much as possible the closet clusters and campus data center faciliKes to commercial clouds. Next is network infrastructure such as rouKng and servers

•  Other obvious money saving pracKces are to power laptop and cell phone charging staKons with roof top solar panels or micro windmills, deploy solar/wind powered WiFi nodes, and use on the move electric charging for campus uKlity vehicles, etc

•  Campus IT folk and NRENs need to educate managers of such funds the IT and networking can play a much more significant role in reducing energy consumpKon and GHG emissions then tradiKonal faciliKes based soluKons

47

Cyber-‐infrastructure in a Carbon Constrained World

hIp://net.educause.edu/ir/library/pdf/ERM0960.pdf

Let’s Keep The ConversaKon Going

Blogspot

Bill St. Arnaud hIp://green-‐broadband.blogspot.com

TwiIer

hIp://twiIer.com/BillStArnaud

E-‐mail list

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