Some Thoughts on The Endeavour Expedition BAA 99

Some Thoughts on The Endeavour Expedition (BAA 99 -07) David Culler Randy Katz The ship of Captain James Cook: His work to build a coherent map of the Pacific was so allencompassing that his competitor, the French Navigator Jean-François de Galaup de La Pérouse, graciously stated “there is little for his successors to do but to admire his work. ”

Why “Endeavour”? “As captain of the Endeavour, Cook would sight and survey hundreds of landfalls that no Westerner had ever laid eyes on. … Cook's epochal voyage aboard the converted collier was destined to bring under George III's sovereignty more land wealth than any single naval victory of the powerful British fleet. But the most important prize of this and the two subsequent voyages. . . was measured not in territory but in knowledge. Patient and methodical where his predecessors had been hasty and disorganized, he would sweep away myths and illusions on a prodigious scale, and in the end would give to the world a long-sought treasure: a comprehensive map of the Pacific. ” Oliver E. Allen, TIME-LIFE books: The Pacific Navigators © 1980

Technology Process Capability Innovation: breakthrough technologies Integration: What we can build into a system Time

Applications Trends Community Communications Sharing Dissemination Publishing Symbolic Finance Numeric Science/Engineering Computation Time

History of Computing Info. Appliances + Wireless Sharing Workstation. LAN Time. Sharing RJE Mainframe Net-less PDA Net-less PC Colocation

Historic Perspective • Technology discontinuities drive new computing paradigms and applications • E. g. , Xerox Alto – 3 Ms--1 mips, 1 megapixel, 1 mbps – Fourth M: 1 megabyte of memory – From time sharing to client-server with display intensive applications • What will drive the next discontinuity? What are the new metrics of system capability?

What’s Important: Shifts in Technology Metrics • Display (human-computer interface) – More ubiquitous I/Os (e. g. , MEMS sensors & actuators) and modalities (speech, vision, image) – How to Quantify? • Connectivity (computer-computer interface) – Not bandwidth but “scaled ubiquity” – Million accesses per day • Computing (processing capacity) – Unbounded capacity & utility functionality (very high mean time to unavailable, gracefully degraded capability acceptable

What’s Important: Shifts in User/Applications Metrics • Cost: Human Effort – Save time – Reduce effort • The Next Power Tools – Leveraging other peoples’ effort/expertise » e. g. , “What did Dave read about disk prices? ” » e. g. , “What did people who buy this book also buy? ”

What is Needed? • Automatic Self-Configuration – Personalization on a Vast Scale – Plug-and-Play • The OS of the Planet – New management concerns: protection, information utility, not scheduling the processor – What is the OS of the Internet? TCP plus queue scheduling in routers • Adapts to You – Protection, Organization, Preferences by Example

Technology Changes & Architectural Implications • Zillions of Tiny Devices – Proliferation of information appliances, MEMS, etc. • “Of course it’s connected!” – Cheap, ample bandwidth – “Always on” networking • Vast (Technical) Capacity – Scalable computing in the infrastructure – Rapid decline in processing, memory, & storage cost • Adaptive Self. Configuration • Loosely Organized • “Good Enough” Reliabilty and Availability • Any-to-Any Transducers (dealing with heterogeneity, over time-legacy--and space) • Communities (sharing)

Adaptive Self-Configuration • Plug-and-Play Networking – No single protocol/API: standardization processes too slow and stifle innovation – Devices probe local environment and configure to interoperate in that environment – “Computer” not defined by the physical box: portals and ensembles • Local Storage is a Cache – Invoke software and apps migrate to local disk • System Learns Preferences by Observation – E. g. , “Privacy by Example: ” owner intervention on first access, observe and learn classification, reduce explicit intervention over time

Loose Organization • Loosely Structured Information – Large volume, easily shared: supports communities • Self-Organized – Too time consuming to do yourself: Organize by example – Individualized & context-dependent filtering • Incremental Access, Eventually exact – Query by concept: “What did Dave read about storage prices? ” » “A close answer quickly is better than a precise answer in the far future”; » Probabilistic access is often “good enough”

“Good Enough” • Availability within human response times is “good enough” – New approaches based on computing in the infrastructure: fast failure detection-restart-fall over exploiting soft state • Inexact answers usually “good enough” – e. g. , web searching, image filtering – e. g. , statistical queries • Graceful Degradation to get “good enough” performance – Under processing load, e. g. eliminate web graphics when server is loaded, and in response to failure

Any-to-Any Transducers • No need for agreed upon/standardized APIs (though standard data types are useful) – If applications cannot adapt, then generate transducers in the infrastructure automatically – Exploits compiler technology – Enhance plug-and-play to the application level • Legacy Support – Old file types and applications retained in the infrastructure

Communities • Scalable Capacity and Control – Vast storage: the system that never forgets – Self-organized and protected “by example” » Incremental model building – Query by concept, imprecise answers are “good enough”, intuitive recall – Utility functionality that is “good enough”

Berkeley Strengths & Weaknesses • Technology Strengths – Gadget design, scalable systems • Applications Strengths – Information Management, Intelligent Processing • Institutional Strengths – Strong engineering/prototypingorientation – Strong track record of industrial interaction and technology transfer • Weaknesses – Not well known in HCI (but ITO BAA implies technology focus is preferred) – Not known for extensive user testing (nontechnology metrics of success? ) – Potential PIs already overcommitted: who can be counted on to deliver?

Process • “Map Out the Expedition”: – Initial funding to do initial planning and research at modest scale (up to $500 K per year) – Initial Community: within EECS Department – Task pool allows PM to pick and choose • Scaled Up Implementation – Testbed option: leverage industrial contacts » University- or City-scale – Additional optional tasks (up to $25 million) » Expanded technology and applications efforts

Expeditionary Expertise “Today, scientists and adventurers are lured by exploratory challenges to all regions of the globe and beyond. The explorer attempts routes of greater difficulty, the researcher perfects field techniques in remote locales. All are breaking new ground in isolated areas of the world usually under harsh conditions over extended periods of time. ” http: //www. expeditionresearch. org/english/ • Technologies/Systems – Computer Systems, Networking, Compilers, Novel Access Devices and Connectivity • Applications – Information management, Intelligent Processing, User Interfaces