Wireless Sensor Network: WSN,CS 80240333 Instructor: CUI Yong,1,Outline,Introduction Motivating applications Enabling technologies Unique constraints Sensor design MAC layer protocol design Scheduled contention Channel polling TDMA Hybrid,2,Embedded Networked Sensing Potential,Medical Environment Recovery,3,Embedded Networked Sensing Potential,4,Micro-sensors, on-board processing, and wireless interfaces all feasible at very small scale can monitor phenomena “up close” Will enable spatially and temporally dense environmental monitoring Embedded Networked Sensing will reveal previously unobservable phenomena,Seismic Structure response,Contaminant Transport,Marine Microorganisms,Ecosystems, Biocomplexity,Embedded Networked Sensing Potential,5,Embedded Networked Sensing Potential,6,Embedded Networked Sensing Potential,Interaction between ground motions and structure/foundation response Current seismic networks not spatially dense enough to monitor structure deformation in response to ground motion, to sample wavefield without spatial aliasing Science Understand response of buildings and underlying soil to ground shaking Develop models to predict structure response for earthquake scenarios. Technology/Applications Identification of seismic events that cause significant structure shaking. Local, at-node processing of waveforms. Dense structure monitoring systems.,7,Field Experiment, 1 km ,38 strong-motion seismometers in 17-story steel-frame Factor Building. 100 free-field seismometers in UCLA campus ground at 100-m spacing,8,Embedded Networked Sensing Potential,Ecosystem Monitoring Understand response of wild populations (plants and animals) to habitats over time. Develop in situ observation of species and ecosystem dynamics. Techniques Data acquisition of physical and chemical properties, at various spatial and temporal scales, appropriate to the ecosystem, species and habitat. Automatic identification of organisms (current techniques involve close-range human observation). Measurements over long period of time, taken in-situ. Harsh environments with extremes in temperature, moisture, obstructions, .,9,Smart Kindergarten Project,10,Enabling Technologies,Embedded,Networked,Sensing,Control system with Small form factor Untethered nodes,Exploit collaborative Sensing, action,Tightly coupled to physical world,Embed numerous distributed devices to monitor and interact with physical world,Network devices to coordinate and perform higher-level tasks,Exploit spatially and temporally dense, in situ, sensing and actuation,11,Unique constraints,Real-time analysis for rapid response. Massive amount of data Smart, efficient, innovative data management and analysis tools. Poor signal-to-noise ratio due to traffic, construction, explosions, . Insufficient data for large earthquakes Structure response must be extrapolated from small and moderate-size earthquakes, and force-vibration testing.,12,Outline,Introduction Motivating applications Enabling technologies Unique constraints Sensor design MAC layer protocol design Scheduled contention Channel polling TDMA Hybrid,13,Sensor design,Passive elements: seismic, acoustic, infrared, strain, salinity, humidity, temperature, etc. Passive Arrays: imagers (visible, IR), biochemical Active sensors: radar, sonar High energy, in contrast to passive elements Technology trend: use of IC technology for increased robustness, lower cost, smaller size COTS adequate in many of these domains; work remains to be done in biochemical,14,Some networked sensor node developments,LWIM III UCLA, 1996 Geophone, RFM radio, PIC, star network,AWAIRS I UCLA/RSC 1998 Geophone, DS/SS Radio, strongARM, Multi-hop networks,WINS NG 2.0 Sensoria, 2001 Node development platform; multi- sensor, dual radio, Linux on SH4, Preprocessor, GPS,UCB Mote, 2000 4 Mhz, 4K Ram 512K EEProm, 128K code, CSMA half-duplex RFM radio,15,Communication/computation technology projection,Assume: 10kbit/sec. Radio, 10 m range. Large cost of communications relative to computation continues,Source: ISI & DARPA PAC/C Program,16,Identifying the energy consumers,Need to shutdown the radio From Tsiatis et al. 2002,SENSORS,CPU,TX,RX,IDLE,SLEEP,RADIO,17,Sensor node energy roadmap,Low-power design Energy-aware design,18,Putting it All Together: Power-aware Sensor Node,Sensors,Radio,CPU,Energy-aware RTOS, Protocols, & Middleware,PA-APIs for Communication, Computation, & Sensing,Dynamic Voltage & Freq. Scaling,Scalable Sensor Processing,Freq., Power, Modulation, & Code Scaling,Coordinated Power Management,PASTA Sensor Node Hardware Stack,19,Future Directions: Sensor-field Level Power Management,Two types of nodes Tripwire nodes that are always sense Low-power presence sensing modalities such as seismic or magnetic Tracker nodes that sense on-demand Higher power modalities such as LOB Approach Network self-configures so that gradients are established from Tripwire nodes to