Quasar Group Sensor Networks Nalini Venkatasubramanian, Univ. of California, Irvine (with slides...

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  • Quasar GroupSensor Networks

    Nalini Venkatasubramanian, Univ. of California, Irvine(with slides from Anish Arora, Sam Madden, Sharad Mehrotra, Rajesh Gupta)

  • Quasar GroupSensor NetworksVarious Sensor ApplicationsOceanographic current monitoring

  • Quasar GroupTaxonomy of Applications (1)Data Access needs of applicationsHistorical dataAnalysis to better understand the physical world

    Current dataMonitoring and control to optimize the processes that drive the physical world

    Future dataForecasting trend in data for decision making

  • Quasar GroupTaxonomy of Applications (2)Predictability of Data accessFixeddata access needs of applications known a-priori

    Unpredictable (ad-hoc)Data access needs of applications not known at any instance of time

    Predictable (continuous)Data access needs of applications can be predicted for some time in the future with high probability

  • Quasar GroupApplication Landscapeno knowledge some knowledge full knowledgeTemporal property of data accessedPredictability of data accessthe presentthe futureEach evening at 8pm predict the temperature for the next 5 daysNotify me immediately when there is a forest fireEvery month, calculate the average humidity in California for the last 30 daysDid the temperature rise above 40oC in the last year?Is Mr. Does newly proposed weather model accurate for 1996-2000?How much snow is there in Aspen?

    Im going surfing on Sep. 30! Will it be windy?Visualize current humidity with Mrs. Does new interpolation scheme.Predict noise levels around the airport if runway 2 becomes operationalthe past

  • Quasar GroupBasic architecture of sensor nodes

  • Anatomy of a sensor(-actuator) nodeSensor(Passive infrared)Actuator(Buzzer)Processor ApplicationNetworkInterfaceAttitude: Freely choose physical variable of interest !Another: Killer apps will multiply when actuation closes the loop

  • Quasar GroupSensor Properties Different CapabilitiesStorageBuilt-in memorySensingComputingMicro-processor or micro-controllerCommunicationShort range radio for wireless communication

  • Quasar GroupSensor Properties Resource ConstraintsLower transmission distances (< 10m) Lower bit rates (typically < kbps) Limited battery capacity

    Radio modePower consumption(mw)Transmit14.88Receive12.50Idle12.36Sleep0.016

  • Quasar GroupSensor Devices todayMIT uAMPS59Mhz to 206 Mhz processor2 radios , capable of transmitting at 1Mbps4KB RAMBerkeley Mica motes8bit, 4Mhz processor40kbit CSMA radio4KB RAM,TinyOS basedA series of sensor nodes developed

  • Quasar GroupSensor OS ConceptsConstrained SchedulingEvent-based(?)Constrained Storage Modelframe per component, shared stack, no heapVery lean multithreadingEfficient LayeringMessaging ComponentinitPower(mode)TX_packet(buf)TX_packet_done (success)RX_packet_done (buffer)Internal Stateinitpower(mode)send_msg(addr, type, data)internal threadCommandsEvents

  • Quasar GroupSensor Network Propertiessmall-scalesensor nodesdense deployment in large numbers

  • Quasar GroupControversies with sensor networksHow is this different from mobile ubiquitous computing?Network-centric vs. edge-centric architecture?Passive sensors vs. smart sensorsA new class of algorithms?Traditional deterministic vs. probabilistic vs. epidemic

  • Quasar GroupWireless Networked Embedded Systems CharacteristicsWirelesslimited bandwidth, high latency (3ms-100ms)variable link quality and link asymmetry due to noise, interference, disconnectionseasier snoopingneed for more signal and protocol processingMobilitycauses variability in system design parameters: connectivity, b/w, security domains, location awarenessneed for more protocol processing Portabilitylimited capacities (battery, CPU, I/O, storage, dimensions)need for energy efficient signal and protocol processing

  • Quasar GroupCapacity of Wireless Sensor NetworksSensor Networksnodes can sense (actuate), compute, communicateat the next level, these nodes and networks can infer, track, correlate and correspondHowever, there are fundamental limits to scaling that have to do with the ad hoc nature of such networksnodes building links and communicating (including relaying, setup and discovery) without a central control

  • Quasar GroupCommunication in Sensor Networks

    Questions we seek to answerHow much information can wireless sensor networks transport? What can be done to maximize this transport?What is the right power level for transport?Where is this control (best) exercised? What is the appropriate network configurationDirect communication (single-hop)Multi-hop communicationDirected diffusion , LAR, GFCluster-based communicationLEACH

  • Quasar GroupChallenges for Sensor NetworksChallenges forSensor NetworksServices for localization, discovery, storage, agreementInjection of application knowledge into sensor network infrastructureIntegration of communication and application specific data processingQuality of data/service Guarantees underresource constraintsAutomatic configuration& error handlingTime & locationmanagement

  • Quasar GroupProjects on Sensor NetworksWebDustRutgersCougarCornellQuasarUC-IrvineAuroraBrown, MIT, Brandeis Univ.SensITMITDuke Univ.Univ. of HawaiiUniv. of WisconsinNorthwestern Univ.Penn State Univ.Auburn Univ.TinyDBUC-Berkeley

  • Specific ExamplesDetect submerged targets in a harbor / ocean environmentDetect chemical or biological attacksDetect forest firesDetect building fires and set up evacuation routesMonitoring dangerous plantsMonitoring social behavior of animals in farms and natural habitatsMonitoring salinity of waterMonitoring cracks in bridgesBathymetry of ocean groundSpace explorationTracking dangerous goodsShooter LocalizationPacemakers for heart and brainCamera-equipped pills for health diagnosticsEpilepsy monitoring and suppression


  • Application ScenariosBorder Monitoring:Detect movement where none should existDecide target classes, e.g., foot traffic to tanksIdeal when combined with towers, tethered balloons, or UAVs

  • ExScal scenarios (continued)Construction Detection:Detect anomalous activity E.g., cars go by often, but no one should stop or start diggingRequires persistent surveillance and in-network pattern matching

    Movement in Tunnels:The ultimate environment for defeating long range sensing

    Urban Operations:Tactical Situational AwarenessMovement indoors and between buildingsRapid dissemination to combatants

  • Key issues at extreme scaleFor large area, how to achieve :

    cost effective coverage ( minimum # of nodes)scale sensing & communication rangeslower power consumptionefficient coverage

    robust, reliable, timely & accurate executionoptimize services for scenario requirement tolerance to deployment errors & component faults

    low human involvement ( minimum # of touches, easy operation, monitoring & (re)configuration)

  • State of the marketplace:Commercial adoption is growing gradually

  • Examples of other military Concept of Operations:Shooter localization

  • Quasar GroupWhat are the Choices?

  • Quasar GroupSensor systems in this lectureLayered approachDistributed sensor networksChallenges in managing large networks of sensors to meet application requirementsSensor Database ManagementChallenges in Query Processing over sensor networks

  • Quasar GroupDistributed Computing Infrastructure for SensorsDesigning Distributed Sensor Architectures Server oriented -- data migrates to server from sensorsStore or not store (stream)When should data migrate How should should data migrate in its original raw form or in some aggregated form. Distributed approachData does not migrate, requests/Queries migrate Tiny DB approach, Dimension ApproachDesigning Middleware Support for Sensor NetworksEnergy-EfficiencyReal-timeFault tolerance

  • Quasar GroupQuery Processing in Sensor NetworksQueries Processing over Sensor Databases Taxonomy of queriesLifetime queries, aggregation queries, approximate queries, set based queries Where do queries ariseAt the server, fully distributed at any nodeQuery semanticsWhat does a query mean? Exact semantics not very clear.Query Processing techniquesAnswering Approximate Queries over Approximate RepresentationAnswering Queries in the networkDistributed Query Answering Data Stream processing & Dynamic Data

  • Quasar GroupDesign Issues in Sensor Devices

    HiPC 2003, Hyderabad, India

  • RequirementsCost

    Lifetime (when almost always on, when almost always off)

    Performance:Speed (in ops/sec, in ops/joule)Comms range (in m, in joules/bit/m)Memory (size, latency)

    Capable of concurrent operation

    Flexibility (?)

    Reliability, security, size, packaging

  • Types of sensor-actuator hardware platformsRFID equipped sensors

    Smart-dust tagstypically act as data-collectors or trip-wireslimited processing and communications

    Mote/Stargate-scale nodesmore flexible processing and communications

    More powerful gateway nodes, potentially using wall power

  • A Closer Look

  • Recent 802.15.4 PlatformsFocused on low power

    Sleep - Majority of the timeTelos: 2.4mAMicaZ: 30mA


    Telos: 290ns typical, 6ms maxMicaZ: 60ms max internal oscillator, 4ms external

    ProcessTelos: 4MHz 16-bitMicaZ: 8MHz 8-bit

    TI MSP430Ultra low power1.6mA sleep460mA active1.8V operationStandards BasedIEEE 802.15.4, USB

    IEEE 802.15.4CC2420 radio250kbps2.4GHz ISM band

    Ease of development and TestProgram over USBStd connector header

    UCB TelosXbow MicaZ

  • Stargate

  • Quasar Gr