Recent Topics in Computer Networking Wireless Sensor Networks Introduction and Applications



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Platzhalter für Bild, Bild auf Titelfolie hinter das Logo einsetzen Recent Topics in Computer Networking Wireless Sensor Networks Introduction and Applications Lars Wolf, Felix Büsching, IBR-CM Winter Term 2012/13

Outline Motivation Terms Design considerations Challenges WSN Applications L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 2

WSN Motivation Various visionary concepts like Ubiquitous Computing (also others influenced the field) 1988: Notion Ubiquitous Computing Introduced and defined by Mark Weiser, XeroxParc Ubiquitous everywhere Ubiquitous: economically, in arbitrary amount available Mark Weiser (1952-1999) 1991 The Computer for the 21st Century Article in Scientific American Vision: Computers become so much of our daily live that we do not take notice of them any longer Ubiquitous Computing enhances computer use by making computers available throughout the physical environment, while making them effectively invisible to the user L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 3

Ubiquitous computing Vision of M. Weiser, XeroxParc Mainframe Comp. Humans share a rare resource Usage explicit, use well prepared User: Experts Personal Comp. Personal Direct usage User: Everybody, supported by experts Ubiquitous Comp. Ubiquitous Implicit usage User: Everybody L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 4

Ubiquitous computing The most profound technologies are those that disappear: (according to Weiser et al.) E.g., Writing: does not require active attention, but the information to be conveyed is ready for use at a glance (Periphery / calm technology) We should not be required to live in computer s world (OS, virtual reality), computers should become invisible and ubiquitous (disappear in background) in our physical world Already computers in light switches, thermostats, stereos and ovens help to activate the world L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 5

Ubiquitous computing Disappearing computing... For such, base technologies are crucial, e.g., Sufficiently powerful processors & storage Wireless communication Sensors Actuators Not for all such applications & scenarios, humans must be involved directly L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 6

WSN Motivation For many applications & scenarios where interaction with environment is taking place: Direct interaction with humans is not necessary or not possible E.g., monitoring industrial processes Humans should be involved in specific situations only E.g., in case of an emergency Or if collected measurement data should be studied, interpreted etc. potentially autonomous operation unless help by human is needed L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 7

WSN Motivation Needs for applications & scenarios interested in interaction with environment: Sensing in environment Computing in environment to process data Communication to transport data Networking to build up larger distributed systems Actuation to influence environment Wireless sensor networks (WSN) Or: Wireless sensor & actuator networks (WSAN) L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 8

WSN Motivation Also a reason: Technology advances make it possible allow for smaller computerized devices with processors, sensors, communication, CMOS miniaturization Micro-sensors (MEMS, materials, circuits) acceleration, vibration, gyroscope, tilt, magnetic, heat, motion, pressure, temp, light, moisture, humidity, barometric chemical (CO, CO2, radon), biological, microradar,... actuators too (mirrors, motors, smart surfaces, micro-robots) Communication short range, low bit-rate, CMOS radios Power Batteries, fuel cells solar, vibration, flow L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 9

Sensor & sensor network Different terms can be used, also depending on discipline Sensor: device which allows sensing of the environment (delivers some relatively simple output) Sensor system: capable to do some processing In WSN field (in computer science & engineering): sensor / sensor node typically includes already some processing Often no strict difference between sensor, sensor system, sensor node L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 10

Sensor & sensor network Sensor network consists of some large number of sensor nodes Sources of data Potentially hundreds or thousands of nodes Sensor nodes cooperate to fullfill their tasks Sensor nodes are deployed in the environment (phenomenon to be observed) or close to it Sensor nodes are resource constraint limited in power, computational capacities, memory, Sensor nodes are prone to failures e.g., it may not hurt if a node dies if WSN is still operational L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 11

Sensor & sensor network: further elements Actuators Control some in-field device Needed to form control loops and have an impact on the environment Aggregating nodes Process and aggregate data received from several nodes Sink nodes Interested in data from sensor nodes Connect WSN to backend systems L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 12

Sensor & sensor network: further elements Backend systems for further processing, analysis, Also for more complex processing, long-term data storage, Networks links between above elements Sensor node to sensor node Sensor node to sink node Sink node to backend Typically different technologies L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 13

Examples for WSN structures L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 14

Promising applications for WSNs Machine and vehicle monitoring Sensor nodes in moveable parts Monitoring of hub temperatures, fluid levels Health & medicine Long-term monitoring of patients with minimal restrictions Intensive care with relative great freedom of movement Intelligent buildings, building monitoring Intrusion detection, mechanical stress detection Precision HVAC (Heating, Ventilating and Air Conditioning ) with individual climate Environmental monitoring, person tracking Monitoring of wildlife and national parks Cheap and (almost) invisible person monitoring Monitoring waste dumps, demilitarized zones and many more: logistics (total asset management, RFID), telematics WSNs are quite often complimentary to fixed networks! L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 15

WSN design considerations / design space Deployment of nodes and WSN in general random vs systematic, manual vs. automatic Mobility of nodes static vs mobile; occasional vs continuous; active vs passive Node s cost, size, resources brick vs matchbox vs grain Heterogeneity within WSN & among nodes homogenous vs heterogeneous wrt type, capabilities,... of nodes, tasks,... L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 16

WSN design considerations / design space Communication approaches radio vs light vs... Infrastructure Infrastructure support used vs completely ad hoc Network topology single-hop vs multihop Coverage sparse vs dense L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 17

WSN design considerations / design space Connectivity regularly connected vs intermittent vs sporadic Network size 10 vs 100 vs 1000 vs 10000 vs 100000 Lifetime day vs month vs year vs decade QOS requirements none vs real-time L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 18

WSN design space: Example network topologies single- vs. multihop Single-hop (star) topology: Direct communication of every sensor node with sink / base station Issues: Perhaps large transmission power needed, connectivity, Multi-hop topology Some sensors serve as relays Issues: Potentially lower transmission power, higher coverage, Needs more complex topology control, routing, L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 19

Challenges in Wireless Sensor Networks Many challenges in WSN, e.g., Energy constraints Unreliable communication Unreliable sensors Deployment Scalability, coverage, density Limited computation power (Re-) Programmability Maintainability Distributed execution L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 20

Challenges in Wireless Sensor Networks: Often not independent Processing characteristics Computation power Throughput Processing Electrical characteristics Energy consumption Energy dissipation Electronics Physics Physical characteristics Shape, ergonomics, robustness Dimensions, weight (also of power source) Lifetime L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 21

Challenges in WSNs: Energy How can energy be supplied? Batteries How to replace batteries? Energy harvesting Light (solar), temperature gradients, motion, vibrations,? Accept limited life-time of sensor node Necessary lifetime due to mission? L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 22

Challenges in WSNs: Energy Energy consumption: ALL parts of sensor node and WSN system are important Node as well as network design energy efficiency important within all parts of sensor node & network design Sensing Processing data Storage of data Transmitting data Receiving data L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 23

Challenges in WSNs: Energy To reduce consumption, sensor node should only be active if really needed sleep otherwise Typical modes controller: Active, idle, sleep radio mode: Turn on/off transmitter/receiver, both different modes possible, e.g., several sleep modes Good operational points? When to put which part into sleep? E.g., from when to when put receiver asleep? L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 24

Challenges in WSNs: Deployment & Self-Management Ways to deploy sensor nodes into their environment: Random E.g., dropped from airplanes Systematic E.g., installed at specific places to be monitored Mobile nodes Active or passive (e.g., wind, water) May compensate for unsettled areas Can move to interesting places L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 25

Challenges in WSNs: Deployment & Self-Management Especially if deployed randomly, sensor node should be able to: determine location detect neighboring nodes and determine their identity configure node parameters discover route(s) to base station initiate sensing responsibility Nodes must be prepared for unattended operation once deployed, WSN must operate without human intervention adapt to changes in topology, density, and traffic load adapt in response to failures (not necessarily also for systematic deployments and more tight controlled scenarios) L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 26

Challenges in WSNs: Security Some WSNs monitor critical infrastructure or carry sensitive infos desirable targets for attacks Attacks from inside / from outside target wireless communication / nodes Difficulties to protect against attacks due to remote and unattended operation wireless communication lack of advanced security features (due to cost, form factor, energy, ) L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 27

Challenges in WSNs: Security Conventional security techniques often not feasible due to their requirements computational, communication, and storage requirements new solutions needed for intrusion detection encryption key establishment and distribution node authentication L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 28

WSN compared to MANETs Commonalities with MANETs (typically) self-organization, multi-hop Typically wireless, should be energy efficient Differences to MANETs Applications: MANET more powerful, more general WSN more specific Devices: MANET more powerful, higher data rates, more resources WSN rather limited, embedded, interacting with environment Scale: MANET rather small (some dozen devices) WSN can be large (thousands) Basic paradigms: MANET individual node important, ID centric WSN network important, individual node may be dispensable, data centric Further issues: Mobility patterns, Quality-of Service, Energy, Cost per node L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 29

Applications for Wireless Sensor Networks Many different application areas studied in WSN community, e.g. as shown in the following Wildlife Monitoring Body Area Networks & Ambient Assisted Living Firefighters Structural Health Monitoring Production processes: GINSENG Many others exist (not shown here) like Traffic control / Management of parking lots Volcanoes / mountains / glaciers monitoring Agriculture Surveillance (civil & military) L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 30

Wildlife Monitoring: Rhinopithecus roxellana Monitoring Real WSN deployment to monitor and track monkeys Protected animals No invasive (e.g. RFID) method possible Identification by sound Pattern matching to identify individual animals Tracking by camera sensors Wake-up camera by change in RSSI L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 31

Rhinopithecus roxellana Monitoring System Architecture L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 32

BAN: Body Area Networks L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 33

Habitat Monitoring L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 34

Fire detection with WSNs - Motivation Moderate surface fire (FWI = 14) Very intense surface fire (FWI = 24) Developing active fire (FWI = 34) FWI Fire Weather Index Depends on temperature & relative humidity Measurable with simple and cheap sensors (at least temperature) L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 35

Fire detection with WSNs System Architecture L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 36

Structural Health Monitoring - Motivation L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 37

Illinois Structural Health Monitoring Project (ISHMP) Jindo-gun, South-Korea 2009, Photography by MEMSIC, from http://blog.memsic.com/2009/11/structural-health-monitoring-part-2-software.html L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 38

Structural Health Monitoring Gathering Accelerometer data at Cable, Deck and Pylon L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 39

GINSENG Control of production processes in refinery E.g., constant monitoring of pipes Close valves before critical condition is reached Reduces maintenance effort & production cost Improve safety and reduce environment hazards L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 40

GINSENG In GALP refinery in Portugal: currently approx. 35000 sensors and actuators to perform monitoring of industrial operations such as leakage detection, measurement of pressure in the pipes, fluid levels... Reduce cost of cabled sensors, but guarantee reaction in certain time ensure stable operation L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 41

IBR Sensor Floor L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 42

IBR Sensor Floor - Architecture One sensor node is connected to 4 load sensors (via Strain Gauge Board) One floor tile is monitored by 4 load sensors One load sensor monitors 4 floor tiles L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 43

IBR Sensor Floor - Applications Front legs of the chair Sit down Stand up Rear legs of the chair L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 44

WSN-Applications: some student projects of past & current WSN-lab INGA-Sports (Wii-Mote like game controller) Sensorfloor-Tennis Juggling pins Weather stations with data mules Monkey Lights Lite EASI Home automation ingarider bike computer Regatta tracing Blinkenlights Lift monitoring L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 45

WSN Applications: Summary Different use cases Specific sensor nodes Specific sensors Different challenges Energy Size Robustness Network scale Communication ranges Specialized hardware L. Wolf, F. Büsching, IBR-CM RTN - WSN Introduction & Applications 46