Development of Complex Curricula for Molecular Bionics and Infobionics Programs within a consortial* framework**
Consortium leader
PETER PAZMANY CATHOLIC UNIVERSITY
Consortium members
SEMMELWEIS UNIVERSITY, DIALOG CAMPUS PUBLISHER
The Project has been realised with the support of the European Union and has been co-financed by the European Social Fund ***
**Molekuláris bionika és Infobionika Szakok tananyagának komplex fejlesztése konzorciumi keretben
***A projekt az Európai Unió támogatásával, az Európai Szociális Alap társfinanszírozásával valósul meg.
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Ad hoc Sensor Networks
Localization algorithms and strategies for wireless sensor networks
Érzékelő mobilhálózatok
Lokalizációs algoritmusok és stratégiák vezeték nélküli hálózatok számára
Dr. Oláh András
Lecture 9 review
• Technological motivations
• The role of routing
• Algorithmic background: the Bellman-Ford algoirthm and its distributed operation
• Routing in WSNs
• Packet forwarding in WSNs
• Conclusions
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Outline
• Motivations of localization
• Challenges in WSN
• Taxonomy of location systems
• Localization algorithms
• Accuracy requirements
• Available localization systems
• Tracking in WSN
Why is localization important?
• It is a fundamental component for many other services
– GPS does not work everywhere
– Smart Systems – devices need to know where they are – Geographic routing & coverage problems
– People and asset tracking
– Need spatial reference when monitoring spatial phenomena
• In many WSN application we are interested in identifying the exact location:
– Where has something happened ? – Where is an Object ?
• Determining the location of the sensor node based on other sensor nodes with known fixed locations called (beacon nodes)
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Challenges in WSN
• Physical layer imposes measurement challenges
– Multipath, shadowing, sensor imperfections, changes in propagation properties (RSSI based localization)
• Extensive computation aspects
– Many formulations of localization problems, how do we solve this optimization problem? We have to solve the problem on a memory constrained processor.
– How do we solve the problem in a distributed manner?
• Networking and coordination issues
– We are using it for routing [→ see Chapter 9], it means we have routing support to solve the problem!
• System Integration issues
– How do you build a whole system for localization?
– How do you integrate location services with other applications?
Real Time Location Systems
• The wireless devices are becoming more and more integrated into our daily lives.
• Wireless devices are becoming more context aware: a system is context aware if it uses contexts to provide relevant information and services (time, location, temperature, speed, orientation, biometrics, audio/video recordings, etc.) to the user, where relevancy depends on the user’s tasks.
• Between these variables that define a context, location is probably the most important inputs that define a specific situation.
• Localization serves as an enabling technology (Real Time
Location Systems) that makes numerous context-aware
services and applications possible (Location Based Services).
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Taxonomy of location systems
• Signaling scheme
– Infrared signal (inexpensive, low power; it is susceptible against sunlight; it cannot penetrate through obstructions )
– Optical signal (LoS, low power, it is affected by sunlight, it provides high accuracies in the short ranges (10m))
– Ultrahang jelek (high accuracies in the short range, inexpensive in LoS conditions, power hungry)
– Radio frequency (most commonly used, it can penetrate through obstacles and can propagate to long distances.)
• UWB, CDMA, OFDM, etc.
• Cellular systems, WLAN, WPAN, RFID, WSN
• Location estimation unit
– handset-based (self-positioning, eg.: GPS)
– network-based (remote-positioning, eg.: WSN)
• Indoor versus outdoor localization
Taxonomy of location systems (cont’)
• Localization type:
– Active Localization: system sends signals to localize target.
– Cooperative Localization: the target cooperates with the system.
– Passive Localization: system deduces location from observation of signals that are “already present”.
– Blind Localization: system deduces location of target without a priori knowledge of its characteristics.
• Centralized versus distributed
• Software-based versus hardware-based
• Relative coordinate versus absolute coordinate
• Based on performance
– accuracy vs. precision, calibration, cost, energy consumption, sensitivity, self organization capability, delay, datarate, etc.
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• Position-related parameters:
– received signal strength (RSS)
P(d)=P0−10nlog10(d/d0) – angle of arrival (AOA)
ri(t)=αs(t − τi) + ni(t)
τi ≈ d/c +(li sin ψ)/c, ahol li = l(Na + 1)/2 − i) – time-of-arrival (TOA)
correlation based, synchronization is needed – time difference of arrival (TDOA)
Taxonomy of location systems (cont’)
The localization algorithm
• Cell ID localization (the nearest reference node)
• Geometrical methods
– Triangulation (at least three nodes)
– Trilateration (in 2D at least three node, in 3Dat least four nodes) – Multilateration
• Statistical methods
• Fingerprint based or pattern-matching
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Computation models
• Each approach may be appropriate for a different application
• Centralized approaches require routing and leader election
• Fully distributed approach does not have this requirement
Accuracy requirements
Applications Range Accuracy
Core apps.
Sports tracking (NASCAR, horse races, soccer) 150m 10-30cm
Cargo tracking at large depots 300m 300cm
Children in large amusement parks 300m 300cm
Animal tracking 300m 150cm
Military
Military training facilities 300m 30cm
Military search and rescue: lost pilot, man overboard, coast guard rescue operations
300m 300cm
Civil
Tracking guards and prisoners 300m 30cm
Aircraft landing systems 300m 30cm
Tracking firefighters and emergency responders 300m 30cm
Supermarket carts 150m 30cm
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Measurements technologies
• Available Technologies: Bluetooth, Cellular, Satellite, Television, Wi-Fi, ZigBee, Ultra Wide Band, RFID, Infrared, Ultrasound, Laser
• Ultrasonic ToA
– Common frequencies 25 – 40KHz, range few meters (or tens of meters), avg.
case accuracy ~ 2-5 cm, lobe-shaped beam angle in most of the cases Wide- band ultrasonic transducers also available, mostly in prototype phases
• Acoustic ToA
– Range – tens of meters, accuracy =10cm
• RF ToA
– Ubinet UWB claims = ~ 6 inches
• Acoustic AoA
– Average accuracy = ~ 5 degrees (e.g acoustic beamformer, MIT Cricket)
• RSSI based localization
– WSN: Accuracy = 2-3 m, Range = ~ 10m – 802.11: Accuracy = ~3m
Available localization systems
Technology Location method Accuracy Remarks
GPS ToA satellite based 1-5m Expensive, Not works indoors Ekahau
(WLAN)
RSS-based pattern
matching 1m No extra cost over existing wireless LAN structure, extensive utilities Microsoft
RADAR
RSS-based pattern
matching 3-4m Scalability problems, no extra cost over existing wireless LAN structure
LOKI
(WLAN) Closest AP cell size Installed as a free software. Used for locating the closest restaurant
Ubisense TDOA and AOA 30cm Maximum tag-sensor distances greater than 50m
Indoor GPS AOA 1mm
Laser positioning system for indoors.
Transmission range expandable from 2 to 300 m.
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Available localization systems: WSN
Technology Location method Accuracy Remarks
Active Badges
Infra-red-based proximity of wearable badges to predeployed sensors
Room-size
Installation costs, cheap tags and sensors, sunlight and fluorescent interference,
Active Bats Ultrasound ToA 9cm Ceiling sensor installation costs Cricket RSS and ultrasound-
based localization 1m $10 beacons and receivers, installation costs
SpotON RSS-based ad-hoc localization
Depends on cluster size
$30 per tag, inaccuracy of RSS metric
Tracking in WSN
• Tracking mobile targets involves finding out the location of mobile targets based on wireless sensor nodes with known positions (tracing the path).
• Given the locations of the nodes and accurate range information to the target, it is straightforward to determine the target's position.
• Traditional tracking applications tend to be split into two separate phases:
– Localization phase: the network is localized using a specialized algorithm.
– Tracking phase: after localization completes, target positions are estimated based on the discovered sensor positions.
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Summary
• Location is probably the most important inputs of context aware systems.
• Common characteristic of numerous location system: each of them is wireless system.
• Network-based services that integrate a derived estimate of a mobile device’s location or position with other information so as to provide added value to the user.
• Most location-based services will include two major actions: (1) Obtaining the location of a user, and (2) Utilizing this information to provide a service.
• The accuracy and precision requirements of location-based applications are highly dependent on the application characteristics.
• There are numerous localization technologies currently available which have different ranges, accuracy levels, costs, and complexities.
• Next lecture: Applications of ad hoc and sensor networks
