Loading presentation...

Present Remotely

Send the link below via email or IM


Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.



Localization in Wireless Sensor Networks

Ahmed Emam

on 1 June 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of WSN

Localization in WSN What Why Problem Definition Localization-Basics Difference between Localization Measurement Techniques and Algorithms Localization Measurement Techniques Angle of Arrival Measurements Distance Related Measurements RSS Profiling Techniques Amplitude Response Phase Response Time Related RSS Light House Offline Map Online Map Algorithms Range Based Algorithms Range Free Algorithms AOA Amplitude Response Phase Response Distance Related Measurements TOA TDOA RSS Light House Approach RSS Profiling Works by constructing a Map of the signal strength behavior in the Coverage Area Online Map Offline Map Algorithms Localization Methods Information Requirements Network Structure Hardware Requirements Proximity based Range based Probabilistic based Absolute Localization Relative Localization Static Mobile Range Based Algorithms Min - Max Multilateration Ring Overlapping Circles Maximum Likelihood Range Free Algorithms Optimum DV-Hop Algorithm GPS - Free Algorithm DV-Hop Algorithm Small amount of Anchor Nodes Steps: Anchor Nodes - Broadcast Average Hop Size Blindfolded Nodes - Calculate physical Distance Optimization: Triangulation Algorithm GPS-free Algorithm Assumptions Phase 1
Local coordinates Phase 2
Global Coordinates All sensors are stationary. So the network topology is fixed.

There are no landmarks in the network.

All sensors are homogeneous, with the same technical characteristics, and especially the same transmission range.

All sensors have enough energy to accomplish a node localization algorithm.

All sensors use omnidirectional antennae.

All the wireless links between sensors are bidirectional.

There are no base stations to coordinate or supervise activities among sensors. No centralized controller. Some Considerations Global Coordinate System - via Transformation Matrix (Affine Transformation) Flip Ambiguity Conclusions Energy Consumption Basics Additional Algorithms 3D Algorithm - SWARM Optimization Heuristic Method for Localization Two Objective HS for distance and connectivity based Localization Node Capture Attack and Defense Applications Underwater Healthcare Cattle Monitoring Outline Introduction
Localization Techniques
Localization Algorithms
State of the Art Algorithms
Conclusions Choosing the Localization Algorithm is highly affected by the Application and the Available Resources. Real-life applications involve 3D and hence more realistic Algorithms are still required. Most Researchers are targeting the Anchor Free Algorithms and enhancing their accuracy, in addition to possible 3D realization. By: Eng. Ahmed Emam Presented to : Dr. Ahmed Akl [1] B. F. ,. B. D. A. Guoqiang Mao, "Wireless sensor network localization techniques," Computer Networks, vol. 51, pp. 2529 - 2553, 2007.
[2] D. (. R. S. P. Anil A. Agashe, "An optimum DV Hop Localization Algorithm for Variety of Topologies in Wireless sensor Networks," International Journal on computer Science and Engineering, vol. 4, pp. 957 - 961, 2012.
[3] L. W. a. Q. Xu, "GPS-Free Localization Algorithm for Wireless Sensor Networks," Sensors, vol. 10, pp. 5899 - 5926, 2010.
[4] J.-H. C. S. Z. Zhong Zhou, "Efficient localization for large-scale underwater sensor networks," Ad Hoc Networks, vol. 8, pp. 267 - 279, 2010.
[5] J. S.-L. ,. M. ,. I.-T. ,. S.-S. R.-V. Diana Manjarres, "On thedesignofanoveltwo-objectiveharmonysearchapproachfor distance and connectivity based localization in Wireless Sensor Networks," Engineering Applications of Artificial intelligence, vol. 26, pp. 669 - 676, 2013.
[6] A. T. H. F. M. a. B. S. Mohamadreza Shahrokhzadeh, "A Heuristic Method for Wireless Sensor Network Localization," Procedia Computer Science, vol. 5, pp. 812 - 819, 2011.
[7] K. L. Aline Baggio, "Monte Carlo localization for mobile wireless sensor networks," Ad Hoc Networks, vol. 6, pp. 718 - 733, 2008.
[8] N. M. Gholami, "An artificialneuralnetworkapproachtotheproblemofwirelesssensors network localization," Robotics and Computer Integrated Manufacturing, vol. 29, pp. 96 - 109, 2013.
[9] I. J. A. K. S.H. Jokhio, "Node capture attack detection and defence in wireless sensor Networks," IET Wireless sensor systems, vol. 2, no. 3, pp. 161 -169, 2011.
[10] G. Q. S. M.-L. L. J.-l. Y. M. WEI Nuo, "Three-dimensional localization algorithm of wireless sensor networks base on particle swarm optimization," The Journal of China Universities of Posts and Telecommunications, vol. 19, pp. 7 -12, 2012.
[11] C. M. H. Y. L. V. D. Juan Ignacio Huircána, "ZigBee-based wireless sensor network localization for cattle monitoring in grazing fields," Computers and Electronics in Agriculture, vol. 74, pp. 258 - 264, 2010.
[12] M. C. L. B. M. C. M. T. Alessandro Redondi, "An integrated system based on wireless sensor networks for patient monitoring, localization and tracking," Ad Hoc Networks, vol. 11, pp. 39 - 53, 2013.
[13] W. D. a. C. Poellabauer, Fundamentals of Wireless Sensor Networks - Theory and Practice, Wiley, 2010.
[14] R. Masiero, "RSSI Based Tracking Algorithms for Wireless Sensor Networks: Theoretical Aspects and Performance Evaluation," 2006 - 2007.
[15] Z. Y. Yunhao Liu, Location, Localization and Localizability, NewYork: Springer, 2011. References
Full transcript