The Endeavour Expedition: Computing and Communications at the eXtremes

1. The Endeavour Expedition: Computing and Communications at the eXtremes Professor Randy H. Katz IBM Research Visit 15 June 2000 405 Soda Hall

2. Massive Cluster Clusters The Very Large The Very Small Gigabit Ethernet Server Client Scalable, Available Internet Services Information Appliances MEMS The eXtremes New System Architectures New Enabled Applications Diverse, Connected, Physical

3. Presentation Outline • Expedition Motivation • The Needed Revolution in Computing and Communications • Packing for the Expedition • Project Organization • Base Exploration plus Extended Expeditions • Summary and Conclusions

4. Background • PITAC Report: “Information Technology Research--Investing in Our Future” • Create a strategic initiative in long-term information technology R&D • Priorities: Software, Scalable Information Infrastructure, High-End Computing, Socioeconomic Impacts • DARPA (and Industry) as Patron • Chart potential “revolutions” in information technology, with promise to achieve dramatic improvements in computing and applications in 21st Century • Technology discontinuities drive new computing paradigms, applications, system architectures • E.g., Project MAC, DARPAnet, Xerox Alto • What will drive the next discontinuity?

5. The Endeavour Expedition:Motivation and Goals • Exploiting IT to enhance understanding • Make it dramatically more convenient for people to interact with information, devices, and other people • Supported by a “planetary-scale” Information Utility • Stress tested by challenging applications in decision making and learning • New methodologies for design, construction, and administration of systems of unprecedented scale and complexity • Figure of merit: how effectively we amplify and leverage human intellect • Technical Approach: Pervasive Information Utility, based on “fluid systems,” enabling new approaches for problem solving & learning

6. Why “Endeavour”? • To strive or reach; a serious determined effort (Webster’s 7th New Collegiate Dictionary); British spelling • Captain Cook’s ship from his first voyage of exploration of the great unknown of his day: the southern Pacific Ocean (1768-1771) • Brought more land and wealth to the British Empire than any military campaign • Cook’s lasting contribution: comprehensive knowledge of the people, customs, and ideas that lay across the sea • “He left nothing to his successors other than to marvel at the completeness of his work.” • Software and resources as a fluid: pools, floods, rivers, eddies, containers, ...

7. Signing On to the Expedition • “Difficulties are just things to overcome.” • "Men [and Women] wanted for Hazardous Journey. Small wages, bitter cold, long months of complete darkness, constant danger, safe return doubtful. Honour and recognition in case of success." • Sir Ernest Shackleton, Legendary Antarctic explorer who lost not a single person on two highly perilous expeditions to reach the South Pole (which he never reached!) • Business UNusual: Research seminars, experimental courses, new synthesis of existing courses

8. Expedition Assumptions • Human time and attention, not processing or storage, are the limiting factors • Givens: • Vast diversity of computing devices (PDAs, cameras, displays, sensors, actuators, mobile robots, vehicles); No “average” device • Unlimited storage: everything that can be captured, digitized, and stored, will be • Every computing device is connected in proportion to its capacity • Devices are predominately compatible rather than incompatible (plug-and-play enabled by on-the-fly translation/adaptation) • Tremendous innovations in technology; yet a comprehensive system architecture is lacking

9. Expedition Challenges • Managing Attention is the Killer App • Not corporate processing but management, analysis, aggregation, dissemination, filtering for the individual • Create Knowledge, not Data • Not management/retrieval of explicitly entered information, but automated extraction and organization of daily activities • Information Technology as a Utility • Continuous service delivery, on a planetary-scale, on top of a highly dynamic information base • Beyond the Desktop • Community computing: infer relationships among information, delegate control, establish authority

10. Information Appliances: Many computers per person, MEMs, CCDs, LCDs, connectivity Information Appliances: Scaled down desktops, e.g., CarPC, PdaPC, etc. Revolution Evolution Evolved Desktops Servers: Integrated with comms infrastructure; Lots of computing in small footprint Servers: Scaled-up Desktops, Millennium Mem BANG! Display Smart Spaces Disk Camera Mem Display Display Display mProc Camera Smart Sensors Disk Keyboard Information Utility mProc Server, Mem, Disk Computing Revolution WAN PC Evolution The Coming Revolution

11. Information Devices Beyond desktop computers to MEMS-sensors/actuators with capture/display to yield enhanced activity spaces InformationUtility InformationApplications High Speed/Collaborative Decision Making and Learning Augmented “Smart” Spaces: Rooms and Vehicles Design Methodology User-centric Design withHW/SW Co-design; Formal methods for safe and trustworthy decomposable and reusable components “Fluid”, Network-Centric System Software Partitioning and management of state between soft and persistent state Data processing placement and movement Component discovery and negotiation Flexible capture, self-organization, and re-use of information Expedition Approach

12. Alex Aiken, PL Eric Brewer, OS** John Canny, AI David Culler, OS/Arch Michael Franklin, DB* Joseph Hellerstein, DB Michael Jordan, Learning* Anthony Joseph, OS Randy Katz, Nets John Kubiatowicz, Arch James Landay, UI Jitendra Malik, Vision George Necula, PL* Christos Papadimitriou, Theory David Patterson, Arch Kris Pister, Mems** Larry Rowe, MM Alberto Sangiovanni-Vincentelli, CAD Doug Tygar, Security Robert Wilensky, DL/AI The Endeavournauts:Interdisciplinary, Technology-Centered Expedition Team *Speaking in New Faculty Perspectives Session ** Speaking in Keynote Session

13. D e s I g n M e t h o d o l o g y Applications Rapid Decision Making, Learning, Smart Spaces: Collaboration Rooms, Classrooms, Vehicles Information Utility Fluid Software, Cooperating Components, Diverse Device Support, Sensor-Centric Data Mgmt, Always Available, Tacit Information Exploitation (event modeling) Base Program Information Devices Option 1: Sys Arch for Diverse Devices MEMS Sensors/Actuators, Smart Dust, Radio Tags, Cameras, Displays, Communicators, PDAs Option 2: Oceanic Data Utility Option 3: Capture and Re-Use Option 4: Negotiation Arch for Cooperation Option 5: Tacit Knowledge Infrastructure Option 6: Classroom Testbed Option 7: Scalable Safe Component-Based Design Organization: The Expedition Cube

14. Base Expedition: Leader Katz • Broad but necessarily shallow investigation into all technologies/applications of interest • Primary focus on Information Utility • No new HW design: commercially available information devices • Only small-scale testbed in Soda Hall • Fundamental enabling technologies for Fluid Software • Partitioning and management of state between soft and persistent state • Data and processing placement and movement • Component discovery and negotiation • Flexible capture, self-organization, info re-use • Limited Applications • Methodology: Formal Methods & User-Centered Design

15. System Architecture for Vastly Diverse DevicesLeader Culler • Design Issues for “Small Device OS” • Current: managing address spaces,thread scheduling, IP stack, windowing system, device drivers, file system, APIs, power management • How can OSs for tiny devices be made radically simpler, manageable, and automatically composable? • Devices of Interest: Dust Motes

16. Open Clients Clients Clients Clients Servers Clients Clients Servers Servers The Internet “The Large”: Service-Centric Platform Arch Infrastructure Services • Enable distributed creation/deployment of scalable, available services • Service registry, aggregate execution env., transparency • Persistent distributed data structures • Massive fluid storage (“Oceanic” Storage) • Adaptive high-bandwidth flows (rivers) • Build infrastructure via composition of services

17. “The Small”: Radically Simple OS for Management & Composition • Basic Assumptions: • Communication is fundamental • Direct “user interface” is the exception not the norm • Critical resource is scheduling data movements, not arbitrary threads of computation • Tiny OS: Little more than an FSM • Commands: event stream merged with sensor/actuator events • General thread compiled to sequence of bounded atomic xacts • Constant self-checking and telemetry • Rely on the infrastructure for complex processing • Correctness-by-construction techniques for cooperating FSMs (tie in to HW/SW co-design)

18. Ubiquitous devices require ubiquitous storage Consumers of data move, change access devices, work in many different physical places, etc. Needed properties: Strong Security Coherence Automatic replica management and optimization Simple and automatic recovery from disasters Utility model Confederations of (Mutually Suspicious) Utilities Canadian OceanStore Sprint AT&T Pac Bell IBM IBM Implementation & Deployment of Oceanic Data Info UtilityLeader Kubiatowicz

19. OceanStore Architecture/Technology • Name and Data Location • Issue: Find nearby data without global communication • Approach: Data location is aform of gradient-search of local pools of data (use of attenuated Bloom-filters) • High Availability and Disaster Recovery • Issue: Eliminate backup as independent/fallible technology • Approach: Erasure-codes/mobile replicas provide stable storage for archival copies and snapshots of live data • Introspective Monitoring and Optimization • Issue: Optimize performance on a global scale • Approach: Monitoring and analysis of access/usage relationships • Rapid Update in Untrusted Infrastructure • Issue: Updates should not reveal info to untrusted servers • Approach: Incremental cryptographic techniques/oblivious function techniques to perform update

20. Managing Data Floods Never ends: interactive direction Big: data reduction/aggregation Unpredictable: scale of devices and nets not behave nicely Builds on CONTROLand River/Eddy System Early answers, interactivity, online aggregation Information processing via massively parallel, adaptive dataflows Extended to wide-area: operator placement, reordering Telegraph Data Manager Distributed Storage Manager based on event flow and state machines Continuously adaptive dataflow with applications to sensor data and streaming media Sensor-Centric Data Management for Capture/ReuseLeader Hellerstein

21. Negotiation Architecture for Cooperating ComponentsLeader Wilensky • Cooperating Components • Self-administration through auto-discovery and configuration among confederated components • Less brittle/more adaptive systems • Negotiation Architecture • Components announce their needs and services • Service discovery and rendezvous mechanisms to initiate confederations • Negotiated/contractural APIs: contract designing agents • Compliance monitoring/renegotiation/non-compliance recovery • Graceful degradation in response to environmental changes

22. Smart Spaces Camera Display Display Camera Smart Sensors Tacit Knowledge Infrastructureand Collaborative ApplicationsLeaders Canny/Joseph/Landay • Exploit information about the flow of information to improve collaborative work • Capture, organize, and place tacit information for most effective use • Learning techniques: infer communications flow, indirect relationships, availability/participation to enhance awareness and support opportunistic decision making • New applications • 3D “activity spaces” for representing decision-making activities, people, & information sources • Visual cues to denote strength of ties between agents, awareness levels, activity tracking, & attention span • Electronic Problem-based Learning in Enhanced Physical and Virtual Learning Spaces

23. User Interfaces and Design ToolsJames Landay and John Canny • Future devices won’t have PC-style UI • Extreme range of devices • Small or embedded in environment • Often w/ “alternative” I/O & w/o screens • Special purpose applications, e.g., Info Appliances • Lots of devices per user, all working in concert • Key Technologies • Tacit information analysis algorithms • Design tools that integrate • “Sketching” & other low-fidelity techniques • Immediate context & tacit information • Interface models

24. Safe Component Design Leader Sangiovanni • Correctness by Construction • Safe partitionings of communicating subcomponents placed in wide-area • Builds on on-going work in embedded systems design • Compositions of Third Party Components • Safety enforcement technologies • Design and development methodologies • Builds on Necula’s Proof Carrying Code • Trust and Assurance • Integrated use of secure tokens for rights management, economic protocols/auctions, support for mobile code, ... • Secure protocol design & deployment based on super-fast model-checking/automatic generation from requirements

25. Network Infrastructure Experimental Testbeds Soda Hall IBM WorkPad Smart Dust Velo Nino LCD Displays MC-16 Motorola Pagewriter 2000 CF788 Pager WLAN / Bluetooth Smart Classrooms Audio/Video Capture Rooms Pervasive Computing Lab CoLab H.323 GW GSM BTS Wearable Displays TCI @Home Adaptive Broadband LMDS Millennium Cluster CalRen/Internet2/NGI Millennium Cluster

26. Putting It Together Devices Utility Applications 1. eXtreme Devices 2. Data Utility 3. Capture/Reuse 4. Negotiation 5. Tacit Knowledge 6. Classroom 7. Design Methods 8. Scale-up Component Discovery & Negotiation Fluid Software Info Extract/Re-use Self-Organization Decision Making Group Learning

27. Summary and Conclusions • 21st Century Computing • Making people’s exploitation of information more effective • Encompassing eXtreme diversity, distribution, and scale • Computing you can depend on • Key Support Technologies • “Fluid software” computational paradigms • System and UI support for eXtreme devices • Pervasive, planetary-scale system utility functionality • Active, adaptive, safe and trusted components • New “power tool” applications that leverage community activity • Broad multidisciplinary team spanning the needed applications, evaluation, and system technology skills • Culture of large-scale, industry-relevant high impact research projects

28. Industrial Collaborators SRI