Designing Reliable Networked Embedded Systems Jan Beutel, ETH Zurich National Competence Center in Research – Mobile Information and Communication Systems

Trends in Information and Communication New Applications and System Paradigms Large-scale Distributed Systems Centralized Systems Networked Systems Internet

The State of Wireless Sensor Network Design More an “art” than a coordinated effort yielding predictable results First generation research provided the proof-of-concept –Performance is poor –Causes are not fully understood –We are often lacking the necessary (scientific) rigor Contributions in this talk –System architecture –Development tools and design methodology –Application case study [Phil Levis, Stanford] Upcoming Keynote at EWSN 2009 Wireless Sensor Networks: Time for Real-Time? John A. Stankovic

THE BTNODE PLATFORM System Architecture for Sensor Networks

BTnodes – Research Impact & Technology Transfer A system solution for fast-prototyping sensor network applications  BTnut System Software  Webpage & mailing list  Installer CDROM  Developer kit & tutorial BTnode rev1 BTnode rev2 BTnode rev3 Mote-class devices  Dual-radio (Bluetooth and ISM band low-power)  TinyOS compatible  Commercialized with industrial partner [SENSYS2003/2004, EWSN2004] 100+ scientific publications based on or related to BTnodes

DISTRIBUTED TEST AND VALIDATION Development Tools and Methodology

Methodology and Development Tools Continuous Integration Testbeds Physical Emulation Advanced Software Engineering Best practices in enterprise-level SW development Regression (unit) testing Extending the Logical View Detailed physical characterization Control of the environment Physical stimulation Control of resources Execution on Real Platforms Distributed, native execution Influence of the environment Remote reprogramming Stimuli and log file analysis

Testbed – The Deployment-Support Network Target Sensor Network DSN Testbed Key Differentiators Distributed observers Mobility: Wireless, battery powered DSN Testbed Functionality Remote reprogramming Extraction of log data Stimuli, e.g. fault injection Time synchronization [SenSys2004, IPSN2005, EWSN2007] Centralized logging Detailed behavioral analysis

DSN Impact – Automated Test Case Generation Detailed control, analysis and replay of simulation and testbed Developed and in-use at Siemens Building Technologies, Zug, CH –Protocols for high reliability wireless applications (fire alarm) [DCOSS2007,INSS2007/2008]

Regression Testing Using Continuous Integration On code change applications are built from scratch and analyzed –Standard practice in enterprise level software development –Deeper understanding of long term development trends –Service to the TinyOS community, increasing software quality TinyOS-2.x regression builds over the last 2 years at ETHZ [

WSN Design and Development Tools Virtualization & Emulation  EmStar arrays [Ganesan2004,Cerpa03/04]  BEE [Chang2003,Kuusilinna2003] Scale Reality Figure abridged from D. Estrin/J. Elson Simulation  TOSSIM [Levis2003]  PowerTOSSIM [Shnayder2004]  Avrora [Titzer2005] Test Grids  moteLab [Werner-Allen2005]  Twist [Handziski2006]  Kansei [Dutta2005] Can we Emulate Reality in the Lab? DSN Wireless Testbed

Physical Emulation Architecture Influence of power sources/quality Detailed physical characterization Emulation of environment and resources –Temperature Cycle Testing (TCT) –Controlled RF attenuation –Sensor stimuli and references Integration and automation with DSN Testbed [EmNets2007]

Visualizing Long Term Development Trends – Power

Assertions based on reference traces/specification Integrated with each build (regression testing) Detailed Tracing – Validation using Formal Bounds [WEWSN2008,SUTC2008]

Test and Validation – Research Outlook Past accomplishments –Developed a baseline infrastructure –Involved in numerous interesting case studies –Gained valuable experience and lots of data Large quantity of data requires automation and tools Fundamental differences in networked embedded systems require novel approaches –Unreliable wireless medium –Distribution nature –Tight embedding in the environment Recent focus on formalization of our methods –E.g. by using Uppaal for trace analysis

THE PERMASENSE PROJECT A Compelling Application Driving Technology Research

PermaSense – Aims and Vision Geo-science and engineering collaboration aiming to: –provide long-term high-quality sensing in harsh environments –facilitate near-complete data recovery and near real-time delivery –obtain better quality data, more effectively –obtain measurements that have previously been impossible –provide relevant information for research or decision making, natural hazard early-warning systems

PermaSense Deployment Sites 3500 m a.s.l. A scientific instrument for precision sensing and data recovery in environmental extremes

PermaSense – Matterhorn Site Details Site of recent rockfall due to extreme warming (07/2003) ~25 nodes Different sensors –Temperatures, electrodes, crack motion, ice stress, water pressure Environmental extremes –−40 to +65° C, ΔT ≦ 5° C/min –Rockfall, snow and ice, avalanches Long-term reliability –1-60 min. DAQ duty-cycle – ≧ 99% data yield –3 years unattended lifetime

PermaDAQ: Precision Sensing and Data Recovery Sensor node architecture –Shockfish TinyNode584 –Customized sensor interface board –Modular sensor concept –1 GB storage (redundancy and validation) –Single battery power supply (~300 uA power budget) TinyOS based on Dozer system [submitted to IPSN2009]

Dozer Low-Power System Integration Dozer ultra low-power data gathering system –Beacon based, 1-hop synchronized TDMA –Optimized for ultra-low duty cycles System-level, round-robin scheduling –“Application processing window” between data transfers and beacons –Custom DAQ/storage routine time jitter slot 1slot 2slot k data transfer contention window beacon courtesy of R. Wattenhofer [IPSN2007]

Physical Reality Impacts Sampling Performance Storage duration Temperature ADC duration Watchdog resets

Sensor Station Mounted on the Mountain

Powerful embedded Linux 4 GB storage, all data duplicated Solar power (2x 90W, 100 Ah, ~3 weeks) GPRS connectivity, 2 nd backup modem PermaSense – Base Station Installation

Site Visit & Maintenance in November 2008

Base Station and Solar Panels On Matterhorn

Real Challenges of Sensor Networks Revisited System Integration Correct Test and Validation Actual DataInterdisciplinary Team

PermaSense Achievements – Current Status Dozer integration successful –Best-in-class low power –DAQ vs. COM power consumption –Extreme installation effort (time) –Relative relaxation of multihop requirement Continuous data since mid July Media attention First joint geo-science publications Started data-integration with the Swiss-Experiment [NICOP2008] 148 uA average power

Acknowledgements BTnode core team –Matthias Dyer, Oliver Kasten, Kay Roemer, Matthias Ringwald PhD students –Matthias Woehrle, Andreas Meier, Matthias Keller PermaSense/Swiss-Experiment collaboration –ETHZ, EPFL, Uni Basel, Uni Zurich, University Paderborn, SLF, Art of Technology Funding –SNSF (NCCR MICS), FOEN, CCES/Microsoft Research (Swiss-Experiment) Further information and publications – –