1Wireless Sensor NetworkRabi MahapatraBackground• Advancement of integration between “tiny embeddedprocessors, wireless interfaces, and “micro-sensors” basedon MEMS led to emergence of wireless sensor network.• Characterized by their ability to monitor the physicalenvironment through ad-hoc deployment of numerous tiny,intelligent, wirelessly networked sensor nodes.2• Large number of heterogeneous sensor devices– Ad Hoc Network• complex sensor nodes with– communication, processing, storage capabilitiesWhat is Wireless Sensor NetworksEmerging applications• Indoor Settings: condition based maintenance ofequipment in factory• Outdoor environment:– Monitor natural habitats– Remote ecosystems– Forest fires– Disaster sites– Defense armaments– Spy microsats3Challenges of WSN• Requirements: small size, large number, tetherless and lowcost. Hence constrained by– Energy, computation and communication• Small form factors => prohibits large long lasting batteries• Cost & energy => low power processors, small radios withminimum bandwidth & small transmission ranges.• Ad-hoc deployment => no maintenance and batteryreplacement• Increase NW lifetime => No raw data to gateway forcomputationTopics to be discussed• Simulation tools on WSN• A simulation architecture overview• Sensor node model & framework of SN• Battery model• Case studies• Bonus points4Existing SimulatorsJavaSim:• Pros– Very modular– Easy to use• Cons– Geared for wired inter-networks– No wireless supportGlomoSim:• Specific for mobile wireless networks.• Built as a set of libraries. The libraries are built in Parsec( a C-baseddiscrete event simulation language).• Layered architecture with easy plug-in capability.Existing Simulators• NS-2: De facto standard for network simulations– Does support wireless simulations– A primitive energy model is present.– Lots of documentation.– Uses Tcl to specify the Components, and Otcl to glue themtogether.Cons:– Difficult to use and learn– Supposedly more useful for getting statistics for lower levelprotocols.– Originally built for wired networks, later extended for wireless.– Supposedly, does not work well for large topologies.5Status of simulators• Other simulator: OpNET• All these tools are not equipped to capture all the aspectsof interests in sensor networks.Current Simulator: SensorSim from UCLA• Extension to NS - 2.• Provides battery models, radio propagation models andsensor channel models.• Provides a lightweight protocol stack.• Has support for hybrid simulation.• Must be integrated with NS - 2.6SensorSim Architecture Overview• Sensor NW has three types of nodes:– Sensor nodes: monitor immediate environment, with manytransducers– Target nodes: generates various stimuli for sensor nodes– User nodes: client and administration of sensor network• Separate channels:– Sensor channels: communication among sensor nodes and target– Network channels: to user node or gateways and onwardtransmission to other network.– Concurrent transmission possible– Easier to model complex behavior of sensor nodes, reaction tomultiple sensor signals.Sensor Network Model architectureSensor channelWireless channelsensorsensorsensorTargetuser7SensorSim Model• Sensor node => one wireless NW protocol stack, one ormore sensor stack corresponds to as many transducers– Sensor stack detects stimuli, process it and forward them toapplication layer, which in turn process and send them to user nodethrough wireless channel– A power model corresponding to energy producing-consuminghardware components is also provided. These component can stayat different power saving and performance states.– The algorithm in both the stacks control the mode of power statesof hardware components. Also, performance of the algorithmdepends on the mode.Sensor Node Model in SensorSimNode Function ModelNetwork Layer Sensor NodeApplicationsPower Model(Energy Consumers and Providers)BatteryModelRadio ModelCPU ModelSensor #1 ModelSensor #2 ModelMAC LayerPhysical LayerSensor LayerWireless ChannelSensor Channel 1NetworkProtocol StackSensorProtocol StackMiddlewarePhysical LayerState ChangeStatusCheckSensor Stack 1Sensor LayerPhysical LayerSensor Channel 28NetworkProtocol StackNetwork LayerMAC LayerPhysical LayerWireless ChannelUser ApplicationUser NodeSensor StackSensor LayerPhysical LayerTarget ApplicationSensor channelTarget NodeFramework of Sensor Network Simulation• Node Placement & traffic generation– Performance of WSN is affected when topology of nodedistribution changes– Application requires a typical distribution (uniform for forest fire,Gaussian for perimeter defense)– Three types of traffics: user-to-sensor (command & queries),sensor-to-user (sensor reporting to user) and sensor-to-sensor(collaborative signal processing before reporting)9Sensor Stack & Channel• Sensor stack is a signal sink that is responsible fortriggering the application layer every time a sensing eventoccurs• Simple sensing scheme to elaborate signal processing canbe implemented on sensor stack• Sensor stack acts as a signal source in Target Node andcontains signatures unique to the model• Sensor channel model the medium of signal transmission(e.g. ground to carry seismic events).• A good simulation tool should model varieties of mediumsand type of sensors ( acoustic, infra red, ultrasonic)Battery Model• Goal: increase the battery life time• Need to study how different aspects of real batterybehavior can affect the energy efficiency of applications• T = C/I, C is capacity in Ah. I is discharge current• Linear Model:– Linear storage of current. Assumes the maximum capacity isunaffected by discharge rate.– Allows user to see efficiency of user application by providing howmuch capacity is consumed. The remaining capacity after td can beexpressed as C = C’ - ∫ I(t)dt integral taken over period t = 0 to td– It assumes that the I(t) will stay same during the period, ifoperation mode does not change (radio switching from Tx toRx)– Remaining capacity is computed when discharge rate is changed10Battery Model• Discharge rate dependent model:– Considers the effect of battery discharge rate on maximumcapacity– Battery capacity efficiency factor K is introduced. K = Ceff /Cmax– Capacity C = K.C’ – I . Td– K varies with current I and is close to 1 when discharge rate is lowand approaches 0 when
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