1. 1 The Endeavour Expedition: Charting the Fluid Information Utility Randy H. Katz, Principal Investigator EECS Department University of California, Berkeley Berkeley, CA 94720-1776

2. 2 Vision/Objective Enhancing human understanding through information technology –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 A pervasive Information Utility, based on “fluid systems technology” to enable new approaches for problem solving & learning

3. 3 Potential Impacts on Commercial Practice 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, constructed on top of a highly dynamic information base Beyond the Desktop –Community computing: infer relationships among information, delegate control, establish authority

4. 4 Proposed Approach Information Devices –Beyond desktop computers to MEMS-sensors/actuators with capture/display to yield enhanced activity spaces Information Utility Information Applications –High Speed/Collaborative Decision Making and Learning –Augmented “Smart” Spaces: Rooms and Vehicles Design Methodology –User-centric Design with HW/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

5. 5 Information Utility Information Devices Applications Collaboration Spaces High Speed Decision Making Learning Classroom Info Appliances E-BookVehicles PDA Handset Laptop Camera Smartboard MEMS Sensor/Actuator/Locator Wallmount Display Generalized UI Support Proxy Agents Human Activity Capture Event Modeling Transcoding, Filtering, Aggregating Statistical Processing/Inference Negotiated APIsSelf-Organizing Data Interface ContractsWide-area Search & Index Nomadic Data & Processing Automated Duplication Distributed Cache Management Wide-Area Data & Processing Movement & Positioning Stream- and Path-Oriented Processing & Data Mgmt Non-Blocking RMISoft-/Hard-State Partitioning

6. 6 Information Devices Information Utility Applications DesIgnDesIgn MethodologyMethodology MEMS Sensors/Actuators, Smart Dust, Radio Tags, Cameras, Displays, Communicators, PDAs Fluid Software, Cooperating Components, Diverse Device Support, Sensor-Centric Data Mgmt, Always Available, Tacit Information Exploitation (event modeling) Rapid Decision Making, Learning, Smart Spaces: Collaboration Rooms, Classrooms, Vehicles Base Program Option 1: Sys Arch for Diverse Devices Option 2: Oceanic Data Utility Option 4: Negotiation Arch for Cooperation Option 5: Tacit Knowledge Infrastructure Option 6: Classroom Testbed Option 7: Scalable Heterogeneous Component-Based Design Option 3: Capture and Re-Use Task Structure Task 1: Base Program Option 1: Systems Architecture for Vastly Diverse Computing Devices Option 2: Implementation and Deployment of the Oceanic Data Information Utility Option 3: Sensor-Centric Data Management for Capture and Reuse Option 4: Negotiation Architecture for Cooperating Components Option 5: Tacit Knowledge Infrastructure and High-Speed Decision-Making Option 6: Information Management for Intelligent Classroom Environments Option 7: Scalable Safe Component- based Design and UI Design Tools Option 8: Scaled-up Field Trials

7. 7 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

8. 8 Option 1: “System Architecture for Vastly Diverse Devices” Leader Culler Distributed control & resource management: data mvmt & transformation, not processing –Path concept for information flow, not the thread –Persistent state in the infrastructure, soft state in the device –Non-blocking system state, no application state in the kernel –Functionality not in device is accessible thru non-blocking remote method invocation Extend the Ninja concepts (thin client/fat infrastructure) beyond PDAs to MEMS devices, cameras, displays, etc.

9. 9 Option 2: Implementation & Deploy- ment of Oceanic Data Info Utility Leader Kubiatowicz Nomadic Data Access: serverless, homeless, freely flowing thru infrastructure –Opportunistic data distribution –Support for: promiscuous caching; freedom from administrative boundaries; high availability and disaster recovery; application-specific data consistency; security Data Location and Consistency –Overlapping, partially consistent indices –Data freedom of movement –Expanding search parties to find data, using application- specific hints (e.g., tacit information)

10. 10 Option 3: Sensor-Centric Data Management for Capture/Reuse Leader Hellerstein Integration of embedded MEMS with software that can extract, manage, analyze streams of sensor-generated data –Wide-area distributed path-based processing and storage –Data reduction strategies for filtering/aggregation –Distributed collection and processing New information management techniques –Managing infinite length strings –Application-specific filtering and aggregation –Optimizing for running results rather than final answers –Beyond data mining to “evidence accumulation” from inherently noisy sensors

11. 11 Option 4: Negotiation Architecture for Cooperating Components Leader 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 and renegotiation –Graceful degradation in response to environmental changes

12. 12 Option 5: Tacit Knowledge Infra- structure/Rapid Decision Making Leader Canny 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, and availability/participation to enhance awareness and support opportunistic decision making New collaborative 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

13. 13 Option 6: Info Mgmt for Intelligent Classrooms Leader Joseph Electronic Problem-based Learning –Collaborative learning enabled by information appliances Enhanced Physical and Virtual Learning Spaces –Wide-area, large-scale group collaboration –Capture interaction once for replay –Preference/task-driven information device selection –Service accessibility –Device connectivity –Wide-area support –Iterative evaluation

14. 14 Option 7: Safe Component Design and UI Design Tools Leader Sangiovanni Information Appliances as an application of hardware/software codesign –Co-design Finite State Machines (CFSMs) –Formal methods to verify safety from faults –Safe partitioning of components into communicating subcomponents placed into the wide-area Model-based User Interface Tools –Information device user interfaces –Multimodal interface design for variety of devices

15. 15 Option 8: Scaled-up Field Trials Leader Katz Testbed Rationale –Study impact on larger/more diverse user community –Higher usage levels to stress underlying architecture –Make commitment to true utility functionality Increasing Scale of Testbeds –Building-Scale »Order 100s individuals –Campus-Scale »Order 1000s individuals –City-Scale »Order 100000 individuals

16. 16 Putting It All Together 1. Diverse Devices 2. Data Utility 3. Capture/Reuse 4. Negotiation 5. Tacit Knowledge 6. Classroom 7. Design Methods 8. Scale-up Devices Utility Applications Fluid Software Info Extract/Re-use Group Decision Making Learning Component Discovery & Negotiation Self-Organization

17. 17 Letters of Support

18. 18 Year 1 Milestones 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;

19. 19 Year 2 Milestones  Complete prototype/refinement component advertisement protocols and I/F negotiation spec language;  Complete prototype implementation/refinement of distributed, persistent storage system;  Complete prototype/refinement sensor-centric data management system;  Initial implementation of cooperative learning and collaboration apps within smart spaces testbed;  Complete implementation sys design tools for early testing;  Complete implementation of second gen fluid software run- time environment based on early use and evaluation;  Design/commence implementation of second gen persistent storage system & sensor-centric data mgmt system;  Delivery of initial experimental results & usability evaluations, & revised architecture document;

20. 20 Year 3 Milestones  Complete second gen persistent storage system and sensor-centric data management system;  Extensive experimental use of apps on second generation components and testbed;  Extensive evaluation and refinement of design methodology applied to second generation fluid software components;  Final refinements and implementation of all software functionality;  Extensive evaluations and measurements of all software functionality;  Delivery of final experimental results and usability evaluations, and final architecture document;