The Endeavour Expedition: 21st Century Computing to the eXtreme

1. The Endeavour Expedition:21st Century Computing to the eXtreme Randy H. Katz, Principal Investigator EECS Department University of California, Berkeley Berkeley, CA 94720-1776

2. The Endeavour Expedition:21st Century Computing to the eXtreme • New Ideas • Systems Architecture for Vastly Diverse Computing Devices (MEMS, cameras, displays) • Wide-area “Oceanic” Data Information Utility • Sensor-Centric Data Management for Capture and Reuse (MEMS + networked storage) • Negotiation Architecture for Cooperating Components (Composable system architecture) • Tacit Knowledge Infrastructure to support High-Speed Decision-Making • Information Management for Intelligent Classroom Environments • Scalable Safe Component-based Design and UI Design Tools R. H. Katz, Principal Investigator, University of California, Berkeley • Impact • Enhancing human understanding by making it dramatically more convenient for people to interact with information, devices, and other people • Supported by a “planetary-scale” Information Utility, stress tested by applications in decision making and learning, achieved thru new methodologies for design, construction, and administration of systems of unprecedented scale and complexity Schedule Usability Studies & Early Tool Design Implementation of UI &Sys Design Tools Tools Release & Final Evaluations Design Methodologies Initial Application Implementation & Evaluation Refined Implementation & Final Evaluation Information Applications Initial Architectural Design & Testbeds Initial Evaluation & 2nd Gen Redesign Final Deployment & Evaluation Information Utility Initial Experiments & Revised Design Doc Initial Architectural Design Document Final Experiments & Architecture Docs Jun 99 Start Jun 00 Jun 01 May 02 End

3. Expedition Goals • Enhancing understanding • 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 • A pervasive Information Utility, based on “fluid systems” to enable new approaches for problem solving & learning

4. Why “Endeavour”? • 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.”

5. 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 such thing as an “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)

6. Expedition Challenges • Personal Information Mgmt is the Killer App • Not corporate processing but management, analysis, aggregation, dissemination, filtering for the individual • People 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

7. Driving Factors • Technology Push • Accelerating developments at the eXtremes: • Cluster-based compute/storage servers • MEMS sensor/actuators, CCD cameras, LCD displays, … • User Pull • More effective community leverage: the next power tool • Desire: • Enhanced interaction, ease of use • Easier configuration, “plug and play” • Less fragile tools, “always there” utility functionality

8. 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 Computing Revolution: Devices in the eXtreme

9. 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

10. Alex Aiken, PL Eric Brewer, OS John Canny, AI David Culler, OS/Arch 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 Interdisciplinary, Technology-Centered Expedition Team

11. 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

12. Base Program: 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

13. 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

14. Service Path Communication-Centric Architecture • Base Scalable Infrastructure • highly available • persistent state (safe) • databases, agents • service programming environment • Active Proxies • connected to the infrastructure • soft-state, bootstrap protocol • transcoding, • Ubiquitous Devices • billions • sensors / actuators • PDAs / smartphones / PCs • heterogeneous • Service Paths • aggregate flows (rivers) • transcoding operators

15. 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

16. “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)

17. Implementation & Deployment of Oceanic Data Info UtilityLeader Kubiatowicz • Ubiquitous devices require ubiquitous storage • Consumers of data move, change access devices, work in many different physical places, etc. • Needed properties: • Strong Security: data must be encrypted whenever it is in the infrastructure • Coherence: too much data for naïve users to keep coherent “by hand” • Automatic replica management and optimization: huge quantities of data cannot be managed manually • Simple and automatic recovery from disasters: probability of failure increases with size of system • Utility model: world-scale system requires cooperation across administrative boundaries

18. Utility-Based Infrastructure Canadian OceanStore • Confederations of (Mutually Suspicious) Utilities • Settlement system among service providers • Buy and sell capacity as needed Sprint AT&T IBM Pac Bell IBM

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. Applications that Enhance Human Activity • Tacit Information Mining: exploit info flows & relationships to improve collaborative work • 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 • Smart Spaces • Electronic collaborative problem-based learning • Physical and Virtual Learning Spaces • Enabled by information appliances • UI design/exploitation of tacit information

21. 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

22. Summary: Putting It All 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

23. Smart Space Testbed Eval. & Initial Design Tools 1st Gen Fluid R/T Environ. 2nd Gen Fluid R/T Environ. 1st Gen Persistent Fluid Store 2nd Gen Persistent Fluid Store Perf Eval 1st Gen Sensor-Centric Info Mgmt 2nd Gen Sensor-Centric IM Perf Eval 1st Gen Comp Neg. Protocols 2nd Gen Negotiation Cooperative Learning App Refine & Use Rapid Decision Making App Refine & Use Final Doc + Experiments Design Document + Early Evaluation Refined Doc + Experiments Base Program Schedule Year 1 Year 2 Year 3 Design Methodology Refined Tools & Flow Information Utility Information Applications

24. Design/initial deployment “smart space” testbed;Initial usability evaluation/refinement; Initial design, prototype, and early evaluation of fluid software run-time environ; Initial design component advertisement protocols & i/f negotiation spec language; Initial prototype/refinement of component advertisement protocols & interface negotiation specification language; Initiate prototype & refinement of distributed, persistent storage system; Initial design of sensor-centric/stream-capture oriented data mgmt system; Initiate prototype & refinement of sensor-centric data mgmt system; Design of distributed, persistent storage system; Initial design of tool flow for infrastructure-embedded software functionality; Initiate implementation of system design tools for early testing; Completion of initial system architecture design document and early system evaluation; Year 1 Milestones

25. Problem Technical Approaches Coherently managing billions of devices where none are “average” Information on demand, available wherever needed, on a global scale, in an untrusted infrastructure Pervasive management of massive stream-oriented information collection/inference in the wide-area Data movement & transformation; Paths, not threads; Persistent state/soft state partitioning; Non-blocking RMI for remote functionality; Support for MEMS devices, cameras, displays, etc. Serverless/homeless/freely flowing data; Opportunistic distribution, promiscuous caching, without administrative boundaries; High availability/disaster recovery, application-specific data consistency, security;Overlapping, partially consistent indices; Data freedom of movement; Expanding “search parties” to find data, using application-specific hints Extract, manage, analyze streams of sensor data; Path-based processing integrated with storage; Data reduction via filtering/aggregation; Distributed collection & processing; “Evidence accumulation” from inherently noisy sensors

26. Problem Technical Approaches Overwhelming config-uration complexity of large & heterogeneous systems Ineffectiveness of technology-mediated collaborative work;Better support for rapid decision making; Enabling Problem-based Learning in Enhanced Physical & Virtual Spaces; Correctness by Construction: Safe Component Design; Dynamic self-configuration: advertise provided services, discover components providing required services, negotiate interface contracts, monitor compliance, eliminate non-performing confederates; Infer communications flow, indirect relationships, availability, participation to enhance awareness & support opportunistic decision making; New collaborative applications: 3D “activity spaces” for representing decision-making activities, people, & info sources; Visual cues “weighting” relationships among agents, awareness levels, activity tracking & attention span Device/net-independent people-to-people comms via pervasive translation/adaptation; Information dissemination technologies; Wide-area information mgmt/access; Formal specifications and methods; Safety enforcement, design/development methods; Proof carrying code/secure protocol verification;

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

28. Industrial Collaborators SRI