Class Note for CMPSCI 677at UMass(7)
Class Note for CMPSCI 677at UMass(7)
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This 11 page Class Notes was uploaded by an elite notetaker on Friday February 6, 2015. The Class Notes belongs to a course at University of Massachusetts taught by a professor in Fall. Since its upload, it has received 15 views.
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Date Created: 02/06/15
Wireless Sensor Networks CMPSCI 677 Lecture 26 Wireless Sensor Networks What are building blocks ofa WSN What is a WSN used for Structure Hardware platforms motes Sensing applications Canonical problems Examples Operating systems 5808 5808 WSN Platforms What are the differences between WSN platforms and typical computers Battery power Goal maximum system lifetime with no rechargereplacement Lowpower radios for communication 10200kbitsec SmaHCPUs Eg 8bit 4k RAM Flash storage Sensors Battery Power Example Mica2 mote Total battery capacity 2500mAH 2 AA cells System consumption 25 mA CPU and radio on Lifetime 100 hours 4 days Alternatives Bigger batteries Solarwindl energy harvesting Duty cycling Low Power Radios ISM band 430 900 or 2400 MHz Varying modulation and protocol Custom FSK Mica2 20 kbits Bluetooth Zigbee 802154 200kbitsec Short range Typically lt1OO meters Low power Eg Chipcon CC2420 917 mAtransmit depending on output level 19 mA receive Listening can take more energy than transmitting Small Example Atmel AVR 8 bit 4 KB RAM 128 KB code flash 2 MIPS 8MHz 8 mA Example Tl MSP430 16 bit sort of 10 KB RAM 48 KB code flash 2 mA CPUs MXPOBUXZHXI BUICK DIAGRAM Fix a m vs Pl 1 a m XlNXlilll a i v i l i mgr 3 Hum 1 cl mm 3 mum Higherpowered processors ARM7 Yale XYZ platform 32 bit 50 MHz gtgt1MB RAM ARM9 StarGate others 32 bit 400 MHz gtgt16MB RAM 5808 Flash Storage Serial NOR flash Raw flash Small serial NOR very low power NAND Pageatati me write No overwrite without erasing Divided into pages and erase blocks Typical values 5128 pages 32 pages in erase block Garbage collection needed to gather free pages for erasing IIIIIII Removable flash media Cooked flash Disklike interface 5128 rewritable blocks Very convenient Higher power consumption Sensors Temperature Humidity Magnetometer Vibration Acoustic Light Motion eg passive IR Imaging cameras Ultrasonic ranging GPS Lotsofothers 5808 Sensor Applications Data driven Distributed computation not communication network Homogeneous All sensors typically participate in the same applications Sensor Patch Sensor Node Typical architecture data collection fusion and transport Transl Network Client Data Browsing and Processin i i Basestation BaseRemote Link Internet i Data Service Canonical WSN Problems Localization Time Synchronization Routing Duty cycled networking Data aggregation 5808 LocaHza on Determining relative or absolute location of a sensor Solutions GPS Ranging and triangulation Radio strength RSSI RF timeof flight interferometry Acoustic timeof flight Directional triangulation Acoustic phase measurement Base Station 1 11 Base Station 3 5 Base a on 2 Problems in Localization GPS is expensive sometimes dif cult to use and power hungry Requires lineof sight to 3 or 4 satellites overhead 80mA for 15 minutes to acquire fix Radio ranging is not accurate Acoustic ranging is limited Range Applications Sensitivity to errors Robust triangulation is hard Path loss racing Distan e 4 lt l 39 m A g k ivrrv L LEW A Z 5808 Time Synchronization Applications Event detection by arrival time Eg gunshot triangulation Duty cycling synchronization External reference GPs wwv Autonomous synchronization Receiverreceiver Senderreceiver Drift estimation Autonomous Synchronization Idea Sample time atA Transmit to B A T A TATOSTmaC Issues TpropTrx B receives TA at TAA Software delays Ttx Trx Channel acquisition Tmac Propagation delay Tprop Clock drift Quartz crystal 50 ppm 50uSs 180mshr Varies with eg temperature 5808 Wireless vs wired More Routing How to handle duty cycling Sleep or go around Sleeping More Routing Network lifetime More packets more battery drain 0 O l packeth gt 93f Sin 0 O 4 packeth 5808 Examples TinyDB 39l39InySQL SELECT ltaggregatesgt ltattributesgt FROM sensors ltbuffergt WHERE ltpredicatesgt GROUP BY ltexprsgt SAMPLE PERIOD ltconstgt ONCE INTO ltbuffergt TRIGGER ACTION ltcommandgt Data Model Entire sensor network as one single in nitelylong logical table sensors Columns consist ofall the attributes de ned in the network Typical attributes Sensor readings Metadata node id location etc Internal states routing tree parent timestamp queue length etc Nodes return NULL for unknown attributes On server all attributes are de ned in catalogXml 5808 12 5808 Acquisitional Query Processing What s really new amp different about databases on motebased sensor networks This paper s answer Long running queries on physically embedded devices that control when and where and with what frequency data is collected Versus traditional DBMS where data is provided a priori For a distributed embedded sensing environment ACQP provides a framework for addressing issues of When where and how often data is sensedsampled Which data is delivered PRESTO Modeldriven Push Insight Models are expensive to PRESTO Proxy create but simple to check Modeling amp Data which can be predicted M does not need to be reported Push if sensor value exceeds or is less Than predicted value by 6 Sensor Data Model Check Data Archiv W PRESTO Sensor 13 5808 Operating Systems What features does an operating system need Unix TinyOS SOS Hardware drivers system init Yes Yes Yes Loadable programs Yes NO Yes File system Yes NO NO Resource allocation eg memory Yes No Yes Processes threads Yes NO Sort of Networking support Yes Yes Yes IPC Yes Yes Yes Event scheduling timers Yes Yes Yes TinyOS amp nesC Concepts New Language nesC Basic unit of code Component Component used for Process Commands SplitPhase Throws Events Has a Frame for storing local state Uses Tasks for concurrency Components provide interfaces Used by other components to communicate with this component Components are wired to each other in a configuration to connect them 14
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