Intel Berkeley and Extreme Networked Systems David Culler 8/12/2002

IRB/XIS2 Where this presentation might go... aka Outline new models of industry/academic research collaboration vast networks of tiny devices in the physical world open infrastructure for emerging planetary-scale services

8/12/2002IRB/XIS3 New model for ind/acad collaboration Key challenges ahead in EECS are fundamentally problems of scale –require level of investigation and engineering beyond what is sustainable within the university and beyond what a company can commit outside product scope –industry possesses key technology and expertise –requires insights from many perspectives A new lab stucture built around deep research collaboration and intimate ties to the EECS department –industry contributes substantial effort of high quality –projects span boundaries –faculty co-direct lab –student / faculty cycles drive the continuous motion Operate in uniquely open fashion

8/12/2002IRB/XIS4 Intel Network of Lablets Concept Network of small labs working closely with top computer science departments around the world on deeply collaborative projects. –Berkeley – extreme network systems –Washington – HCI –CMU – distributed storage –Cambridge Complement the corporate labs –explore off the roadmap, long range, high risk Complement the external-research council –drive projects of significant scale and impact Expand the channel –Bi-directional transfer of people, ideas, technology

8/12/2002IRB/XIS5 lablet mission Leadership role in emerging and important areas Combining the unique strengths of Intel and Univ. Bi-directional exchange of breakthough ideas, technology and people Lablet Novel component technology SRPs University Intel Labs Advanced Applications Advance of the research ecosystem

8/12/2002IRB/XIS6 Berkeley Emphasis Cross-cutting problems of scale. Extreme Interconnected Systems “ endonets” –dense, fine-grain networked systems deeply embedded in or interacting with physical environment –sensor networks –ubiquitous computing architectures –computational fabrics, surfaces, structures “exonets” –broad coverage networked systems at societal scale –world-wide storage systems –composable infrastructure services –massive servers for millions of users

8/12/2002IRB/XIS7 Scale and structure Active day-to-day involvement ~20 full-time Intel Researchers and Engineers –currently 13 ~5 part-time Intel folks 20 faculty, students, visitors, research consultants Two-in-a-box co-directors University Director + Intel Director Report to David Tennenhouse, VP Research Project focused ~6-year projects starting about every two years

8/12/2002IRB/XIS8 Two Major Lab Projects Define and Develop complete ‘network system stack’ for deeply embedded sensor/effector networks –enabling technology –create the community –core architecture, OS, networking, service foundations –demonstrate revolutionary applications Create an Open Laboratory for Widely- distributed “Planetary Scale” Services to explore architecture, services and applications –enabling resource catalyzes community –distributed development effort –foundations: scalable, secure slice-able platform –infra and service design trade-offs (DHT, Dist-storage)

8/12/2002IRB/XIS9 Open Collaborative Research Agreement Master Agreement states –intent: Open –terms, conditions (IP addendum) Research Project Descriptions –what, who, where scope of work defines boundary of openness! –an openness agreement is all about defining reach-through

8/12/2002IRB/XIS10 System Stack for Deeply Embedded Networks

8/12/2002IRB/XIS11 Bridging the Technology-Appln Gap mgmt / diag / debug algorithm / theory service network system architecture prog / data model data mgmt application Monitoring & Managing Spaces and Things technology

8/12/2002IRB/XIS12 Deeply Embedded Networks # nodes >> # people sensor/actuator data stream unattended inaccessible prolonged deployment energy constrained operate in aggregate in-network processing necessary what they do changes over time => must be programmed over the network

8/12/2002IRB/XIS13 Project Activities Core Platform –architecture, TinyOS, Networking –simulation and debugging tools Programming Support –NesC (TinyOS modularity and concurrency) –Cooperating FSMs, atomicity –Macroprogramming Sensor-Network databases –streaming, noisy data, with in-network query processing Delay Tolerant Networking –overlay for diverse, challenged internets Interactive Environments and Things –ambient displays, remote physical communication –context-aware tools for the handicapped Habitat and Environmental Monitoring –dense sensor networks in the hands of life scientists Generic Sensor Kit

8/12/2002IRB/XIS14 Platform Architecture Goal –create a small wireless device that would enable us to explore the system design space, applns to be attempted, and a new research community –develop the architecture in response to observed system design Approach –joined in the series of UCB COTS mote designs »WeC -> Rene -> iDot -> MICA –look to silicon for full architecture New ideas –rich interfaces allow radical system optimizations »analog wake-up, Tx-Rx time synch –federation of accelerators, not dedicate protocol proc. –HW/SW multithreading for low power, passive vigilance service network system architecture data mgmt application technology

8/12/2002IRB/XIS15 Berkeley Wireless Sensor ‘Motes’ Mote TypeWeCReneRene2DotMica DateSep-99Oct-00Jun-01Aug-01Feb-02 Microcontroller (4MHz) TypeAT90LS8535ATMega163ATMega103/128 Prog. Mem. (KB) RAM (KB)0.514 Communication RadioRFM TR1000 Rate (Kbps)1010/40 Modulation TypeOOKOOK/ASK

8/12/2002IRB/XIS16 TinyOS Application Graph RFM Radio byte Radio Packet UART Serial Packet ADC Tempphoto Active Messages clocks bit byte packet Route map routersensor appln application HW SW Example: self-organized ad- hoc, multi-hop routing of photo sensor readings 3450 B code 226 B data Graph of cooperating state machines on shared stack

8/12/2002IRB/XIS17 It is a noisy world after all... Get to rethink each of the layers in a new context –coding, framing –mac –routing –transport, –rate control –discovery –multicast –aggregation –naming –security –... Resource constrained, power aware, highly variable,... Every node is also a router No entrenched ‘dusty packets’ probability of reception from center node vs xmit strength

8/12/2002IRB/XIS18 Example “epidemic” tree formation

8/12/2002IRB/XIS19 Habitat Monitoring Acadia National Park Mt. Desert Island, ME Great Duck Island Nature Conservancy Ongoing research WAN (satcast) LAN sensor nets

8/12/2002IRB/XIS20 Cross-cutting issues? application service network system architecture technology mgmt / diag / debug algorithm / theory prog / data model Programming environments Deep & scalable simulation Algorithm behavior at scale Operating on prob. distributions Fine-Grain Inverse problems Pseudo-imaging Constructive foundations of self-organization data mgmt

8/12/2002IRB/XIS21 The Other Extreme - Planetary Scale Services

8/12/2002IRB/XIS22 Motivation A new class of services & applications is emerging that spread over a sizable fraction of the web –CDNs as the first examples –Peer-to-peer,... Architectural components are beginning to emerge –Distributed hash tables to provide scalable translation –Distributed storage, caching, instrumentation, mapping, events... The next internet will be created as an overlay on the current one –as did the last one –it will be defined by its services, not its transport »translation, storage, caching, event notification, management There will soon be vehicle to try out the next n great ideas in this area

8/12/2002IRB/XIS23 Confluence of Technologies Cluster-based scalable distribution, remote execution, management, monitoring tools –UCB Millennium, OSCAR,..., Utah Emulab, ModelNet... CDNS and P2Ps –Gnutella, Kazaa,...,Pastry, Chord, CAN, Tapestry Proxies routine Virtual machines & Sandboxing –VMWare, Janos, Denali,... web-host slices (EnSim) Overlay networks becoming ubiquitous –XBONE, RON, Detour... Akamai, Digital Island,.... Service Composition Frameworks –yahoo, ninja,.net, websphere, Eliza Established internet ‘crossroads’ – colos Web Services / Utility Computing Grid authentication infrastructure Packet processing, –Anets,.... layer 7 switches, NATs, firewalls Internet instrumentation The Time is NOW

8/12/2002IRB/XIS24 Guidelines (1) Thousand viewpoints on “the cloud” is what matters –not the thousand servers –not the routers, per se –not the pipes, per se

8/12/2002IRB/XIS25 Guidelines (2) and you miust have the vantage points of the crossroads –primarily co-location centers

8/12/2002IRB/XIS26 Guidelines (3) Each service needs an overlay covering many points –logically isolated Many concurrent services and applications –must be able to slice nodes = > VM per service –service has a slice across large subset Must be able to run each service / app over long period to build meaningful workload –traffic capture/generator must be part of facility Consensus on “a node” more important than “which node”

8/12/2002IRB/XIS27 Guidelines (4) Test-lab as a whole must be up a lot –global remote administration and management »mission control –redundancy within Each service will require its own remote management capability Testlab nodes cannot “bring down” their site –generally not on main forwarding path –proxy path –must be able to extend overlay out to user nodes? Relationship to firewalls and proxies is key Management, Management, Management

8/12/2002IRB/XIS28 Guidelines (5) Storage has to be a part of it –edge nodes have significant capacity Needs a basic well-managed capability –but growing to the model should be considered at some –may be essential for some services

8/12/2002IRB/XIS29 Initial Researchers (mar 02) Washington Tom Anderson Steven Gribble David Wetherall MIT Frans Kaashoek Hari Balakrishnan Robert Morris David Anderson Berkeley Ion Stoica Joe Helerstein Eric Brewer John Kubi Intel Research David Culler Timothy Roscoe Sylvia Ratnasamy Gaetano Borriello Satya Milan Milenkovic Duke Amin Vadat Jeff Chase Princeton Larry Peterson Randy Wang Vivek Pai Rice Peter Druschel Utah Jay Lepreau CMU Srini Seshan Hui Zhang UCSD Stefan Savage Columbia Andrew Campbell ICIR Scott Shenker Mark Handley Eddie Kohler

8/12/2002IRB/XIS30 Initial Planet-Lab Candidate Sites Intel Berkeley ICIR MIT Princeton Cornell Duke UT Columbia UCSB UCB UCSD UCLA UW Intel Seattle KY Melbourne Cambridge Harvard GIT Uppsala Copenhagen CMU UPenn WI Chicago Utah Intel OR UBC Washu ISI Intel Rice Beijing Tokyo Barcelona Amsterdam Karlsruhe St. Louis

8/12/2002IRB/XIS31 Approach:Service-Centric Virtualization Virtual Machine Technology has re-emerged for hosting complete desktop environments on non-native OS’s and potentially on machine monitors. –ex. VMWare,... Sandboxing has emerged to emulate multiple virtual machines per server with limited /bin, (no /dev) –ex. ENSim web hosting Network Services require fundamentally simpler virtual machines, can be made far more scalable (VMs per PM), focused on service requirements –ex. Jail, Denali, scalable and fast, but no full legacy OS –access to overlays (controlled access to raw sockets) –allocation & isolation »proportional scheduling across resource container - CPU, net, disk –foundation of security model –fast packet/flow processing puts specific design pressures Instrumentation and management are additional virtualized ‘slices’ –distributed workload generation, data collection

8/12/2002IRB/XIS32 Hard problems/challenges “Slice-ability” – multiple experimental services deployed over many nodes –Distributed Virtualization –Isolation & Resource Containment –Proportional Scheduling –Scalability Security & Integrity - remotely accessed and fully exposed –Authentication / Key Infrastructure proven, if only systems were bug free –Build secure scalable platform for distributed services »Narrow API vs. Tiny Machine Monitor Management –Resource Discovery, Provisioning, Overlay->IP –Create management services (not people) and environment for innovation in management »Deal with many as if one Building Blocks and Primitives –Ubiquitous overlays Instrumentation

8/12/2002IRB/XIS33 Emerging Extreme Internet Wide-Area Broad-Coverage Services Traditional pt-pt Internet Deeply- Embedded Networks

8/12/2002IRB/XIS34 backup

8/12/2002IRB/XIS35 Mission for the Network of Labs Bold new form of Industry-University collaboration that reflects the changing nature of the information age. Conduct the highest quality research in emerging, important areas of CS and IT. Join the unique strengths of Universities and the company in concurrent, collaborative efforts that are both broad in scope and deeply penetrating in exploration. Operate in a uniquely open fashion, promoting a powerful, bidirectional exchange of groundbreaking ideas, technology, and people. Leadership role in the creation of new research ecosystems spanning the continuum from academic study to product development. Labs will be project-focused with an active, constantly evolving agenda involving Intel researchers, University researchers, and members of the larger research community

8/12/2002IRB/XIS36 Berkeley Focus Extreme Interconnected Systems Invent, develop, explore, analyze, and understand highly interconnected systems at the extremes of the computing and networking spectrum - the very large, the very small, and the very numerous Do leading-edge Computer Science on problems of scale, cutting across traditional areas of architecture, operating systems, networks, and languages to enable a wide range of explorations in ubiquitous computing, both embedded in the environment or carried easily on moving objects and people

8/12/2002IRB/XIS37 Current Research Team Hans Mulder – co-director, IA64 Kevin Fall: UCSD, ISI, UCB, NetBoost, Intel –high speed ip networking Alan Mainwaring: TMC, UCB, Sun, Intel –virtual networks, deep scalable network systems Anind Dey: Georgia Tech, aware house –framework for context aware applns, ubicom David Gay: UCB –Prog. Lang. design/Imp for novel comm. layers Wei Hong, UCB, Illustra, Cohera, PeopleSoft –Federated databases Su Ping: Intel –Software Engineering, embedded systems Eric Paulos: UCB –HCI, robotics, ubicomp Timothy Roscoe: Cambridge, Sprint –Operating systems, Distributed Computing, Infrastructure Services Brent Chun: UCB, CIT –cluster systems, resource management Matt Welsh, UCB (Post Doc) –Operating Systems, internet service design Phil Buonodonna, UCB (abd intern) –Storage Area Networks, networks Silvia Ratnasamy, UCB/ICSI (abd) –Networking, P2P Justin Tomilson, Part Time –optimization, IEOR PhD Student Earl Hines – operations mgr

8/12/2002IRB/XIS38 Additional Researchers Joe Hellerstein, Faculty Consultant (next AD) –streaming database, sensor database, P2P Eric Brewer, Faculty Consultant –systems, language design Larry Peterson, Consultant/Sabattical Deborah Estrin, Faculty consultant –internet, multicast, rsvp,...sensor nets Paul Wright, Former Faculty consultant –infopad, BWRC, cybercut

8/12/2002IRB/XIS39 Current Faculty Research Associates James Demmel large-scale comp. sci Michael Franklin Sensor Databases Steven Glaserstructural dynamics Joe HellersteinStreaming Databases John Kubiatowiczplanetary storage James LandayHCI David A Patterson Architecture Kris Pister MEMS, Smart Dust Jan Rabaey Low power systems Satish Rao Distr. Systems Theory Ion Stoika Networking Vivek Subramanian Disposable devices David Wagner Security Kathy YelickParallel Languages Jennifer MankoffHCI Shankar SastryDistributed Robotics