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NBN: The hunt for “silver bullets ” and “killer apps” i .e. it’s now about tools for apps & use, stupid.

NBN: The hunt for “silver bullets ” and “killer apps” i .e. it’s now about tools for apps & use, stupid. University of New England 16 November 2011 Gordon Bell Principal Researcher Microsoft Research, Silicon Valley Laboratory. Observation, bias, and challenge.

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NBN: The hunt for “silver bullets ” and “killer apps” i .e. it’s now about tools for apps & use, stupid.

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  1. NBN: The hunt for “silver bullets”and“killer apps”i.e. it’s now about tools for apps & use, stupid. University of New England 16 November 2011 Gordon Bell Principal Researcher Microsoft Research, Silicon Valley Laboratory

  2. Observation, bias, and challenge • NBN is: Cloud Services as the Silver Bullets. It’s:“Continuous Services” for “Cloud Connected Devices”. • “The Cloud” will drive the NBN • Poster apps e.g. energy grid, education & health are Application, content,data rights limited… look elsewhere • NBN requires new ventures and new usesIt’s now up to engineers, scientists, and entrepreneurs • NBN success should or will be judged by new ventures… and their payoff

  3. NBN: fiber/wireless net connecting mobile and fixed clients to a cloud computing infrastructure for applications & content NBN Mobile Clients Cloud Computing: Services & Content Fixed Clients & Client Nets Television Content

  4. Computer person’s view of NBN:“Continuous Services i.e. apps & Client Connected Devices” Cloud Computing: Services & Content Mobile Clients Connected Devices NBN Fixed Clients & Client Nets Television Content

  5. Outline • NBN from computing perspective: It’s the cloud • The Internet was built for Research… got the Web! • The Cloud” is the next computer class…Bell’s Law • The Internet of Things (& Phones) create the demand • Science apps are critical: 4thparadigm • Engineering apps pay the bills:CSIRO Tasmanian sensor net • Health: is a cloud app … some day • Entrepreneur's & Services. Surveillance, lifelogging, etc. • Tele-x. Sarnoff’s, Metcalfe’s (Vail’s), & Reed’s Laws e.g. face2facebook. Tele-”n”-vision for sports, health

  6. Colin Griffin UNE 9/2011

  7. Ed Feigenbaum, Stanford Faculty Campus. Fiber to the home

  8. A tale of two approaches • NBN US: Massive study re. competition & plan. Result: Let the market build it. • NBN Oz: Minimal study & plan. Result: Just do it.

  9. Courtesy Mary Meeker Presents…

  10. Recalling 1995: First Internet World Keynote… 1,000 attendees Prediction of post www with fiber. The worlds of TV, telecom, and data collide

  11. Net History: Story of Serendipity • ARPAnetc1970 goals: • rlogin; load-, program-, and data-sharing… cost-motivated • Got: • rlogin (remote login) • mail plus as a service carrier.... • bbs/news/chat/muds/moos • ftp (file transfer protocol) and • rpc enabled distributed computing

  12. Games Television world Telephony world VCR Cable provides: TV on demand, internet & POTS AT&T provides: POTS, wireless, DSL..., & TV tbd CDs >97 Wire- less Cable Cable phone Broad- cast LECs Long Dist. LECs TV DBS The Colliding Worlds of TV, Telephony & Datacom a.k.a. Computing & Internet PBX Cable I’net I’net Phone ITV? What about TV as aggregations of channels? How much Aggregation is needed? The Internet LAN PBX RADIO Pvt. WANs clients/ servers Wire- less LANs Datacom world

  13. Video & Convergence…Finally • 90% traffic is video; Neflix 30%, YouTube 20, Bittorent • $1000 Bet: Nat Barrie asserts that by January 2013, the majority of video will come via computer versus conventional TV Broadcast channels that include cable e.g. Foxtel digital and over-the-air channels. • Computer channels include all the video content that is store and forward, on demand e.g. ABC on line, Hulu, Netflix, YouTube via all the digital IP streams e.g.  WiFi, Cable Modems, ADSL, NBN fiber.

  14. The TV “cable bundle” in your hand…

  15. The Cloud is a New Computer Class • “The Cloud” comes in various sizes, shapes, and ownership and rental models • It is so important that nearly all research has to be “cloud washed”

  16. Bell’s Law of Computer Classes… Where we are goingEvery Decade a new class emerges and some die • Every decade a new, lower (1/10th) cost class of computers emerge to cover cyberspace with a • New computing platform • New Interface to humans or something in physical world, “stuff” • New networking and/or interconnect structure • New classes  new apps  new industries • The classes… a decade in price every decade • ‘60s $millions mainframes (central) • ‘70s $10K-100K minis • ‘80s $10K workstations and PCs (personal) • ‘90s $1K The Internet PCs • ‘00s $100s Smartphones & the “cloud” Services … XaaS • ‘10s $10 “the cloud” & small clients (central & person) “The Internet of Things”, WSNs, sensors • ?? ? In body, implantable everything. • ??? ? “the singularity” computers > human

  17. Cloud Computing c2010 … XaaS

  18. ATSE Cloud Computing. Sept. 2010 R1The Commonwealth Government should …ensure a supportive regulatory environment. R2The Commonwealth Government’s Commercialisation …should actively encourage new businesses that are cloud-focused at internet-scale applications. R3The Commonwealth Department of Broadband Communications …to ensure that unnecessary impediments to the uptake of Cloud Computing are minimised. R4Australian universities should expand … to build knowledge and skills in cloud computing. R5 The Commonwealth Government should create and fund an Australian equivalent of the NSF’s Cluster Exploratory Programand the NSF-Microsoft Program to actively encourage cloud computing. R6 The National Research Infrastructure Council (NRIC) should refine its investment plans to reflect the benefits that cloud computing can provide. R7The Commonwealth Government should ensure that proposals for research data storage using Super Science funds have evaluated cloud computing services.

  19. ATSE Cloud Computing ReportSeptember 2010 (find the NBN in this picture)

  20. The Internet of Things= Smart World… devices for health, energy, science, etc. • Things: appliances, platforms, peripherals, WSNs,… phones that have been evolving for decades • Anything, Anytime, Anywhere, Anyway, Always Applications: • Mostly mobile phones, the foreseeable future • scientific sensors for transforming science • networks monitoring and control—water, traffic, power, health/wellness, earth science, … smart(x)

  21. .netgadgeteer Microsoft Gadgeteer

  22. Courtesy Mary Meeker Presents…

  23. Courtesy Mary Meeker Presents…

  24. Functions integrated into cell phones aka Smart Phones aka small form factor devices aka handheld computers TVeBookGeoVector eBook, TVPointing anywhere* Health monitor BodyMedia Multimedia player iPod Smartphone & PC with apps Windows Mobile WWW. Web Browsing Email BlackBerry Programmable platform -PC with apps PocketPC Digital Audio Player Rio & Music svc Camera addition Imaging GPS service GPS service Availability PDA Functionality Palm SMS Service SMS US mobile phones licensed (AMPS) Cellular net handheldgames Gameboy 2002 1979 1983 1992 1995 1995 1997 1998 1999 2000 2002 2002 2003 2007 2010 Increasing bandwidth protocols e.g. GSM, service generations enabler not shown Notes: Audio recording, video capture, videophone, and mobile TV not shown *GPS: location lat, long, alt. 3 axis compass; 6 axis accel. Smartphones are today’ personal mainframes

  25. Complete, 1 mm3 Systems--mote MicroProc Battery Solar cell Xmitter Sensor 5.3 nW

  26. Science and Engineering Apps… • The Fourth Paradigm of scientific discovery • Science and Engineering are both real time • Science closed loop is o(years to decades) • Engineering is for sensing and immediate control

  27. Sensing… Observations by human operators Sharing of data To effect change Sensors* REAL WORLD System *Sensor/effector may be people

  28. Real time Control (ideal sans noise) Plain old closed loop control Model of REAL WORLD System Advice(t+1) Controller (Processing, policies & people) Sensors* REAL WORLD System Effectors* *Sensor/effector may be people

  29. Thousand years ago: science was empirical describing natural phenomena Last few hundred years: theoretical branchusing models, generalizations Last few decades: a computational branch simulating phenomena Today: data exploration branch (eScience) unify theory, experiment, and simulation Data captured by instruments or simulation Processed by software Information/Knowledge stored in computer for enquiry Scientist analyzes database / filesusing data management and statistics Data lives & is accessed forever Jim Gray NRC-CSTB Four Science Paradigms

  30. Synthesizing Imagery, Sensors, Models and Field Data FLUXNET Curated sensor 30GB dataset (960 files) Climate classification ~1MB (1file) FLUXNET curated field dataset 2 KB (1 file) Vegetative clumping ~5MB (1file) NASA MODIS imagery archives 5 TB (600K files) Sizes given are 1 US year 20 US year ~ 1 global land surface year NCEP/NCAR ~100MB (4K files)

  31. Global Scale Reprojection Global Scale Reduction Archive Download Continental US

  32. ModisAzure By the numbers…. • 22 months • 2 CS interns; 1 architect; 1 science intern; 1 senior scientist; 3 hangers-on • 522 K cpu hours • 14 TB upload • 10 TB max storage • 5 TB download • 2.3 B storage operations • 1.3 M re-projected tiles • 25 M reduction files • (TBD) VM scaleup/scaledown operations • (TBD) Lines of (nonMatLab) code • $79K external billing Courtesy Catharine van Ingen

  33. Seed funding from -- minerals and geothermal research at www.pir.sa.gov.au -- Microsoft Research USA Jim Gray Seed Grant -- MSR Azure funding 433,000 hours -- Institute for Minerals and Energy First eScience Lab enabled by cloud computing

  34. Vision: A geologist guiding a drill, using real-time sensing of the sub-surface geology, and updating geological models, while referring to her cloud-based data sets and collaborating with her team back home Geologist in field Compute Modelling on-Demand MT Inversion Seismic Inversion. Joint Inversion. Visualisation. drilling machine control system Data and geologist’sdata integrations. Seismic, Satellite, MT, Petrophysical, Cores, Density, etc. NBN for remote access to compute and historical data guiding Collaboration Sub-surface Sensing– a dozen or more sensors Seismic XRF Resistivity etc Collaborative Cloud Computing Lab (C3L)

  35. Magnetotelluric (MT) imaging • Using the magnetic and electric fields of the earth, MT imaging determines the resistivity structure of a sub-surface area of interest. • It goes deeper (hundred or so Km) than seismic (<2 Km) but does not have the same resolution • Applications • mineral exploration, • water management in mining, • geothermal exploration, • carbon storage, • aquifer research and management • earthquake and volcano studies. (Heinson and Mudge, 2010) A platform technology

  36. Massive parallel processing - peak demand - interactive control-field deployment Parallel programming models are at • Program level • Express data parallelism in MapReduce/Hadoop/DryadLINQ • Job level • Workflow languages define concurrent execution Restructuring of MT processing steps and pulling all parameter inputs to the start, results in parallel processing of station data, and better workflow • Ultimately field deployment at many sites

  37. The South Esk Hydrological Sensor Web: Next-Generation Catchment Management Water for a Healthy Country Andrew Terhorst Tasmanian ICT Centre (Hobart WSM real time) award winner 9 September 2011

  38. Integrating sensor data from multiple agenciesCreating a services infrastructure “bottom up” 2011 iAwards - Sustainability and Green IT

  39. Project goal Develop a prototype water information system made up of two linked sub-systems: • Continuous flow forecast system • Based on emerging Sensor Web standards • Provenance management system • Provides information on how flow forecasts are produced 2011 iAwards - Sustainability and Green IT

  40. Paradigm shift Numerical Models Decision Support Tools Semantic Broker Application Layer Sensor Web Services Layer Physical Sensors, Observation Archives Sensor Layer 2011 iAwards - Sustainability and Green IT

  41. The “killer app”… Health!—my favoritedear to my heart

  42. Sensors with IP On Everything

  43. Cloud service, =1 million mammograms* • Cost of store Amazon $US 0.125 / GB-month • $1.50 / GB-year; $0.15 / 100 MB-year (person) • $150,000 per million person-years • Cost of long term storage will decline • Access is fully distributed, including • Digital X-ray capture stations (2 min. upload/download) • Reading stations can be anywhere, including computers and services in the cloud • Legacy X-ray digitization as needed • Secondary, yet principal benefit: analytics based on age, wt., location, … • * Proposed at AEHR Conference 31 March 2009

  44. Imaging data flow Web-based Image viewer Web-based Image viewer Web-based Image viewer 4 MICROSOFT CLOUD storageHealthVault - image metadata, blog catalog and access keyring Azure - binary image data (original DICOM images, presentation state, compressed pre-views 2 1 5 3 -Embedded -UIS Images are harvested by either Amalga-Embedded or full UIS Images captured within the enterprise are safely and cost-effectively stored in the Cloud – where they can be referenced in multiple use cases and monetized on an ongoing basis Scenarios HealthVault Enterprise to provider Enterprise to patient Enterprise to enterprise Patient to provider (2nd opinion) Enterprise backup Azure

  45. Health continuous sensing devices

  46. BodyMedia Output

  47. c2002

  48. HR, weight, BP, distance,

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