Localization in WSN


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  • TDOA is the location determination method that AT&T uses to locate a caller when they dial 911 from their mobile phone. TDOA calculates the location of a mobile phone by using the difference in the time of arrival of signals at different cell sites.
  • Localization in WSN

    1. 1. Localization in WSN Presented by: Yara Ali Supervised by: Dr. Ahmed Akl Localization in WSN 1
    2. 2. Agenda          Introduction to WSN Localization Usage GPS .. Why not ? Localization methods taxonomy Classifications of Localization Methods Summary Future work References Localization in WSN 2
    3. 3. Introduction to WSN  A large number of self-sufficient nodes  Nodes have sensing capabilities  Can perform simple computations  Can communicate with each other Localization in WSN 3
    4. 4. Introduction to WSN (Cont.)  Beacon (Anchor) node: It’s a node that’s aware of it’s location, either through GPS or manual preprogramming during deployment. Localization in WSN 4
    5. 5. Introduction to WSN (Cont.)  In a Wireless sensor nodes thousands of sensors need to know their position Many applications need position info:  in-home  forest-fire detection  atmospheric (temperature, pressure, … )  military (target detection, …)  police Localization in WSN 5
    6. 6. Introduction to WSN (Cont.)  1. 2. 3. 4. Advantages: It avoids a lot of wiring It can accommodate new devices at any time It's flexible to go through physical partitions It can be accessed through a centralized monitor Localization in WSN 6
    7. 7. Introduction to WSN (Cont.)  1. 2. 3. Disadvantages It's easy for hackers to hack it as we cant control propagation of waves Comparatively low speed of communication Gets distracted by various elements like Blue-tooth Localization in WSN 7
    8. 8. Localization    Localization is a process to compute the locations of wireless devices in a network WSN Composed of a large number of inexpensive nodes that are densely deployed in a region of interests to measure certain phenomenon. The primary objective is to determine the location of the target Localization in WSN 8
    9. 9. Localization (CONT.) Localization in WSN 9
    10. 10. Localization (CONT.) Localization in WSN 10
    11. 11. Usage       Coverage Deployment Routing Location service Target tracking rescue Localization in WSN 11
    12. 12. GPS .. Why not ?   We need to determine the physical coordinates of a group of sensor nodes in a wireless sensor network (WSN) Due to application context and massive scale, use of GPS is unrealistic, therefore, sensors need to self-organize a coordinate system Localization in WSN 12
    13. 13. GPS .. Why not ? (Cont.) 1. 2. 3. 4. Expensive GPS satellite signals are weak (when compared to, say, cellular phone signals), so it doesn't work as well indoors, underwater, under trees, etc. The highest accuracy requires line-of-sight from the receiver to the satellite, this is why GPS doesn't work very well in an urban environment The US DoD (dept of defense) can, at any given time, deny users use of the system (i.e. they degrade/shut down the satellites) Localization in WSN 13
    14. 14. Localization methods taxonomy Localization in WSN 14
    15. 15. 1- Target/Source Localization   Most of the source localization methods are focused on the measured signal strength. To obtain the measurements, the node needs complex calculating process. Localization in WSN 15
    16. 16. 1- Target/Source Localization (Cont.) 1. The received signal strength of single target/source localization in WSN during time interval t: Localization in WSN 16
    17. 17. 1- Target/Source Localization (Cont.) 2. The received signal strength of multiple target/source localization in WSN during time interval t: Localization in WSN 17
    18. 18. 1- Target/Source Localization (Cont.)  The Above methods require transmission of a large amount of data from sensors which may not be feasible under communication constraints. 3-4. The binary sensors sense signals ( infrared, acoustic, light, etc. ) from their vicinity, and they only become active by transmitting a signal if the strength of the sensed signal is above a certain threshold. Localization in WSN 18
    19. 19. 1- Target/Source Localization (Cont.)    The binary sensor only makes a binary decision (detection or non-detection) regarding the measurement. Consequently, only its ID needs to be sent to the fusion center when it detects the target. Otherwise, it remains silent. So, the binary sensor is a low-power and bandwidth-efficient solution for WSN. Localization in WSN 19
    20. 20. Taxonomy Localization in WSN 20
    21. 21. 2- Node Self-localization   Range-based Localization: uses the measured distance/angle to estimate the indoor location using geometric principles. Range-free Localization: uses the connectivity or pattern matching method to estimate the location. Distances are not measured directly but hop counts are used. Once hop counts are determined, distances between nodes are estimated using an average distance per hop and then geometric principles are used to compute location. Localization in WSN 21
    22. 22. 2-1 Range based localization Localization in WSN 22
    23. 23. 2-1 Range based localization (Cont.) 1.   Time of arrival: (TOA) It’s a method that tries to estimate distance between 2 nodes using time based measures. Accurate but needs synchronization Localization in WSN 23
    24. 24. 2-1 Range based localization (Cont.) 2. Time Difference Of Arrival: (TDOA)  It’s a method for determining the distance between a mobile station and a nearby synchronized base station. (Like AT&T)  No synchronization needed but costly. Localization in WSN 24
    25. 25. 2-1 Range based localization (Cont.) 3. Received Signal Strength Indicator: (RSSI)  Techniques to translate signal strength into distance  Low cost but very sensitive to noise Localization in WSN 25
    26. 26. 2-1 Range based localization (Cont.) 4. Angle Of Arrival: (AOA)  It’s a method that allows each sensor to evaluate the relative angles between received radio signals.  Costly and needs extensive signal processing. Localization in WSN 26
    27. 27. 2-2 Range-free localization   DV-Hop is the typical representation It doesn’t need to measure the absolute distance between the beacon node and unknown node. It uses the average hop distance to approximate the actual distances and reduces the hardware requirements. Localization in WSN 27
    28. 28. 2-2 Range-free localization (Cont.)   Adv: Easy to implement and applicable to large network. Disadv: The positioning error is correspondingly increased. Localization in WSN 28
    29. 29. 2-2-1 DV-Hop  1. 2. 3. It is divided into 3 stages: Information broadcast Distance calculation Position estimation Localization in WSN 29
    30. 30. 1-Information broadcast     The beacon nodes broadcast their location information package which includes hop count and is initialized to zero for their neighbors. The receiver records the minimal hop of each beacon nodes and ignores the larger hop for the same beacon nodes. The receiver increases the hop count by 1 and transmits it to neighbor nodes. All the nodes in a network can record the minimal hop counts of each beacon nodes. Localization in WSN 30
    31. 31. 2-Distance calculation  According to the position of the beacon node and hop count, each beacon node uses the following equation to estimate the actual distance of every hop Localization in WSN 31
    32. 32. 3- Position estimation    The beacon node will calculate the average distance and broadcast the information to network. The unknown nodes only record the first average distance and then transmit it to neighbor nodes. The unknown node calculates its location through. Localization in WSN 32
    33. 33. 2-2-1 DV-Hop (Cont.)  Anchors   A-B: 15 3 hops avg hop: 5 flood network with own position flood network with avg hop distance Nodes  4 1 1  B 3 A count number of hops to anchors multiply with avg hop distance Localization in WSN 2 1 3 2 2 1 33 C 4
    34. 34. 2-2-1 Modified DV-Hop Localization in WSN 34
    35. 35. 2-2-2 Pattern Matching Localization   1. 2.  Also called map-based or finger print algorithm. It involves 2 phases: The received signals at selected locations are recorded in an offline database called radio map. It works at the online state. The pattern matching algorithms are used to infer the location of unknown node by matching the current observed signal features to the prerecorded values on the map Localization in WSN 35
    36. 36. Classifications of Localization Methods  The localization techniques can be classified with respect to various criteria: 1. Centralized vs Distributed 2. Range-free vs Range-based 3. Mobile vs Stationary 4. Coarse-grained vs fine-grained Localization in WSN 36
    37. 37. Centralized vs Distributed   Centralized  Data collected in the whole network are transmitted to the central unit that calculates the estimated location of each node in a network. Distributed  Computation is distributed among the nodes  Each node estimates its own position based on the local data gathered from its neighbors. Localization in WSN 37
    38. 38. Range-Free vs Range-Based   Range-Free (connectivity)  Makes no assumption about the availability or validity of such information, and use only connectivity information to locate the entire sensor network.  Hop-Counting Techniques Range-Based (distance)  Defined by protocols that use absolute point to point distance estimates (range) or angle estimates in location calculation. Localization in WSN 38
    39. 39. Mobile vs Stationary  Mobile Stationary Localization in WSN 39
    40. 40. Coarse-grained vs finegrained   Coarse-grained: finding approximate coordinates of nodes in a network so it provide lower precision estimates of this coordinates. Fine-grained: Determining precisely the coordinates but require much more communication and computation efforts. Localization in WSN 40
    41. 41. Summary     WSN .. What & Why ? Distance estimation VS position computation VS localization algorithm Single/Multiple localization in WSN/WBSN Calculating the distance between sensor nodes ( TOA – TDOA – RSSI – AOA ) Localization in WSN 41
    42. 42. Summary    Range-based methods require extra hardware therefore have a higher cost but provide more accurate distance measurements, whereas range-free methods use only connectivity information and so are less accurate. Range-free localization ( DV-Hop , Modified DV-Hop , pattern matching localization ) The localization techniques can be classified with respect to various criteria. They differ on the assumed localization precision, hardware capabilities, measurement and calculation methods, computing organization, the assumed network configuration, architecture, nodes properties and deployment, etc. Localization in WSN 42
    43. 43. Future Work  Few papers investigate multiple-source localization in WSN and WBSN Localization in WSN 43
    44. 44. References 1. http://www.hindawi.com/journals/ijdsn/2012/96 2. http://www.docslide.com/wireless-sensor-netw 3. http://www.docstoc.com/docs/32678966/Loc alization-in-Wireless-Sensor-Network--ELEC-619B-Presentation Localization in WSN 44
    45. 45. References (Cont.) 4.https://www.cs.virginia.edu/~stankovic/psfiles/wsn.pdf 5.http://www.sersc.org/journals/IJCA/vol6_no3/7.pdf 6.http://www.docstoc.com/docs/130374399/Localization -in-Wireless-Sensor-Networks 7. http://www.degruyter.com/view/j/amcs.2012.22.issue2/v10006-012-0021-x/v10006-012-0021-x.xml Localization in WSN 45
    46. 46. Any Questions? Localization in WSN 46
    47. 47. Thank You ! Localization in WSN 47