gps calibrated ad-hoc localization for geosocial networking dexter h. hu cho-li wang yinfeng wang...
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GPS Calibrated Ad-hoc Localization for
Geosocial Networking
Dexter H. Hu
Cho-Li WangYinfeng Wang
{hyhu,clwang,yfwang}@cs.hku.hk
Outline
• Introduction– Mobile Twitter for Geosocial Networking
• Related Work– MCL and Amorphous
• MobiAmorph algorithm
• Performance Evaluation and Analysis
• Discussion
• Conclusion
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Geosocial Networking• From social networking -> mobile social
networking -> geosocial networking– A new type of social networking in which
geographic services and capabilities such as geocoding and geotagging are used to enable additional social dynamics.
• Application Example– Location-planning– Social Shopping– Trip tracking
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Mobile Twitter1. Practical for real life usage and encourage ad-hoc
information sharing, – Mobile social applications will be more meaningful
and location-aware – Twit social events with location information attached.
• Car accident, Taxi call, Voting, Disaster/rescue
2. Localization is possible without the deployment of large infrastructure– Help of GPS-enabled mobile users
3. Under certain mobility model of pedestrians in typical urban environment, accurate GPS information can quickly propagate to non-GPS users
GPS Calibrated Ad-hoc Localization for Geosocial Networking
Usage Scenario and Components
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Usage Scenario and Components (cont'd)
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Localization with Historical Data and Moving Velocity
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Figure 2
possible area
Related Work
• Range-free Localization– Monte Carlo Localization (MCL)
• Posterior distribution of a node’s possible locations using a set of weighted samples
– Amorphous• Similar variant DV-HOP, pop-counting technique
which is similar to distance vector routing. • Each seed broadcasts its location to neighbors and
other nodes try to estimate their distance to seeds
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Outline
• Introduction– Mobile Twitter: Geosocial Networking
• Related Work– MCL and Amorphous
• MobiAmorph algorithm
• Performance Evaluation and Analysis
• Discussion
• Conclusion
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Common Notations
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MobiAmorph Algorithm
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Receive enough fresh information
Localization with Historical Data and Moving Velocity
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Figure 2
possible area
MobiAmorph Algorithm• Relaxed Trilateration:
– Multilateration of Amorphous needs at least 3 reference points. – Location estimating with overlapping circles can still have a
decent estimation even there are only two reference points available.
• Increased coverage.
• Historical Data – Last estimated location to increase accuracy and coverage.
• With relaxed trilateration, only one reference information is need
– Two hop count packet• Increased coverage and accuracy
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Outline
• Introduction– Mobile Twitter: Geosocial Networking
• Related Work– MCL and Amorphous
• MobiAmorph algorithm
• Performance Evaluation and Analysis
• Discussion
• Conclusion
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Performance Evaluation and Analysis
• MobiReal Simulator
• Evaluation Goals:1. Coverage and Accuracy of MobiAmorph with
MCL and Amorphous
2. MobiAmorph under various settings for recommended configuration in real deployment
3. Mobile Twitter’s power/memory consumption by MobiAmorph
GPS Calibrated Ad-hoc Localization for Geosocial Networking
Evaluation Scenarios
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Open Area (100m x 100m)
Street Building(500m x 500m)
Effect of Packet Interval and Seed Ratio in Street and Open Area
Parameter Value
Node Speed (m/s) 1.5, 3, 5
Radio Range (m) 10
Seed Ratio 0.2, 0.3, 0.4, 0.5
Packet Interval 5, 15, 30, 60, 90
Density 30
GPS Calibrated Ad-hoc Localization for Geosocial Networking
Effect of Packet Interval and Seed Ratio in Street and Open Area (cont'd)
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Street Open
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OpenStreet
MobiAmorph Performance on Street Scenario
Parameter Value
Node Speed (m/s) 1.5, 3, 5
Radio Range (m) 10
Seed Ratio 0.2, 0.3, 0.4, 0.5
Packet Interval 5, 15, 30, 60, 90
Density 10, 20, 30, 40
GPS Calibrated Ad-hoc Localization for Geosocial Networking
MobiAmorph Performance on
Street Scenario (cont'd)
21
Mobile Twitter Deployment Evaluationon Android phone
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Outline
• Introduction– Mobile Twitter: Geosocial Networking
• Related Work– MCL and Amorphous
• MobiAmorph algorithm
• Performance Evaluation and Analysis
• Discussion
• Conclusion
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Discussion• Resolution Limitation
– Theoretical limitation for using only connectivity information
• Privacy and Security for Adoption– Malicious seeds– Corrupted relay nodes– Application Message encrypted
• Pedestrian Mobility Model– Urban Pedestrian Flows (UPF)
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Conclusion• Ad hoc localization with the help of GPS
information in urban environment with pedestrians
• We compared MobiAmorph with other two distributed range-free localization algorithms.
• The Mobile Twitter application is developed with the MobiAmorph algorithm on the Android to boost adoption of geosocial networking.
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Thank you! 謝謝!
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