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Density-Aware Hop-Count Localization (DHL) in Wireless Sensor Networks with Variable Density

Density-Aware Hop-Count Localization (DHL) in Wireless Sensor Networks with Variable Density. Sau Yee Wong 1,2 , Joo Chee Lim 1 , SV Rao 1 , Winston KG Seah 1 1 Communications and Devices Division, Institute for Infocomm Research 2 National University of Singapore IEEE WCNC 2005.

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Density-Aware Hop-Count Localization (DHL) in Wireless Sensor Networks with Variable Density

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  1. Density-Aware Hop-Count Localization (DHL) in Wireless Sensor Networks with Variable Density Sau Yee Wong1,2, Joo Chee Lim1, SV Rao1, Winston KG Seah1 1Communications and Devices Division, Institute for Infocomm Research 2National University of Singapore IEEE WCNC 2005 Shao-Chun Wang

  2. Outline • Introduction • Background and Related Work • Density-Aware Hop-Count Localization (DHL) • Simulation Result • Conclusion Shao-Chun Wang

  3. Introduction-(cont.)- • Hop-count localization algorithm • simple • sensor networks are multi-hop • sensors usually have low mobility • packet size is small and constant Reference Node Shao-Chun Wang

  4. Introduction-(cont.)- • conventional hop-count localization algorithms only provide good location estimation if the node distribution in the network is dense and uniform • The node distribution in a sensor network is not always uniform • terrain contour • hostile environment Shao-Chun Wang

  5. Introduction • Goal • improve the accuracy of location estimation when the node distribution is non-uniform Shao-Chun Wang

  6. Background and Related Work-(cont.)- • hop-count localization algorithm • triangulation • distance between a Reference Node (RN) and any node can be estimated by • D = HC x R • D : distance • HC : min. hop-count from the RN • R : transmission range Shao-Chun Wang

  7. Background and Related Work-(cont.)- • Case A Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang

  8. Background and Related Work-(cont.)- • Case B Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang

  9. Background and Related Work-(cont.)- • Case C Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang

  10. Background and Related Work-(cont.)- • Case D Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang

  11. R 2R 3R 4R Background and Related Work-(cont.)- Case D Case C Case B Case A Actual Distance Estimated Distance Shao-Chun Wang

  12. Background and Related Work-(cont.)- • “Ad hoc positioning system (APS)” • Globecom 2001 • DV-Hop

  13. Background and Related Work-(cont.)- • DV-Hop R1,R2,R3:Refernece Node 1.Flooding Beacon: Location Information R2 R3 A R1 Shao-Chun Wang

  14. Background and Related Work-(cont.)- • DV-Hop 2.Each node maintains a table: { Xi , Yi , hi } hi: Min. Hop Count { X1 , Y1 , 2 } { X2 , Y2 , 0 } { X3 , Y3 , 5 } { X1 , Y1 , 3 } { X2 , Y2 , 2 } { X3 , Y3 , 3 } R2 { X1 , Y1 , 0 } { X2 , Y2 , 2 } { X3 , Y3 , 6 } R3 A R1 { X1 , Y1 , 5 } { X2 , Y2 , 6 } { X3 , Y3 , 0 }

  15. Background and Related Work-(cont.)- • DV-Hop 3.Reference Node estimates an average size for one hop R2 75m 40m R3 A R1 100m

  16. Background and Related Work-(cont.)- • DV-Hop 4.Flooding Beacon: Average size for one hop R2 R3 A R1 Shao-Chun Wang

  17. Background and Related Work-(cont.)- • DV-Hop 5.Estimate distance to the three Reference Nodes 6.Node A perform a triangulation to get its location R1: 3 x 16.42 R2: 2 x 16.42 R3: 3 x 16.42 R2 R3 A R1 Shao-Chun Wang

  18. Background and Related Work • The distance per hop is greater in dense regions and smaller in sparse regions Shao-Chun Wang

  19. Density-Aware Hop-Count Localization-(cont.)- • Assumptions • network is connected • sensors have low mobility • each node is assumed to know its number of neighbors Shao-Chun Wang

  20. Density-Aware Hop-Count Localization-(cont.)- • Local density is defined as the number of neighbors • Nngbr • Range ratio • the ratio of hop-distance to the transmission range • μ • Σμ hop-distance Shao-Chun Wang

  21. Density-Aware Hop-Count Localization-(cont.)- • Density categories • p < Nngbr < q Shao-Chun Wang

  22. Density-Aware Hop-Count Localization-(cont.)- Reference Node Forwarding Node Destination Node μ=0.8 Node Σμ= Transmission Range : R μ=0.7 Low density μ=0.6 Medium density μ=0.7 High density μ=0.8 Σμ= μ=0.6 μ=0.6 Σμ= Σμ= A Shao-Chun Wang

  23. Density-Aware Hop-Count Localization-(cont.)- • 1.Flooding Beacon: • Location Information Reference Node Forwarding Node 2. Σμ + μ Destination Node μ=0.8 Node Σμ= Transmission Range : R μ=0.7 Low density μ=0.6 Medium density μ=0.7 High density μ=0.8 Σμ= μ=0.6 μ=0.6 Σμ= Σμ= A Shao-Chun Wang

  24. Density-Aware Hop-Count Localization-(cont.)- • 1.Flooding Beacon: • Location Information Reference Node Forwarding Node 2. Σμ + μ Destination Node μ=0.8 Node Σμ= 0.8 Transmission Range : R μ=0.7 Low density μ=0.6 Medium density μ=0.7 High density μ=0.8 Σμ= μ=0.6 μ=0.6 Σμ= Σμ= A Shao-Chun Wang

  25. Density-Aware Hop-Count Localization-(cont.)- • Hop information update method Shao-Chun Wang

  26. Density-Aware Hop-Count Localization-(cont.)- 3.forwards accumulated range ratio to their neighbors Reference Node Forwarding Node Destination Node μ=0.8 Node Σμ= 0.8 Transmission Range : R μ=0.7 Low density μ=0.6 Medium density μ=0.7 High density μ=0.8 Σμ=1.5 μ=0.6 μ=0.6 Σμ=2.1 Σμ=2.7 A Shao-Chun Wang

  27. Density-Aware Hop-Count Localization 4.Estimate distance to the Reference Nodes D = 2.9 x R Reference Node Forwarding Node 5.Node A perform a triangulation to get its location Destination Node μ=0.8 Node Σμ= 0.8 Transmission Range : R μ=0.7 Low density μ=0.6 Medium density μ=0.7 High density μ=0.8 Σμ=1.5 μ=0.6 μ=0.6 Σμ=2.1 Σμ=2.7 A Shao-Chun Wang

  28. Simulation Results • Range ratio determination • Distance accuracy comparisons • Position accuracy comparisons • Overhead comparisons Shao-Chun Wang

  29. Simulation Results-Range Ratio Determination (cont.)- • 50m x 50m square area • Transmission range : 5m • Ratio range : 0.1 – 0.9 Shao-Chun Wang

  30. Simulation Results-Range Ratio Determination (cont.)- Shao-Chun Wang

  31. Simulation Results-Range Ratio Determination- Shao-Chun Wang

  32. Simulation Results-Distance Accuracy Comparisons- Shao-Chun Wang

  33. Simulation Results-Position Accuracy Comparisons- Shao-Chun Wang

  34. Simulation Results-Overhead Comparisons (cont.)- Shao-Chun Wang

  35. Simulation Results-Overhead Comparisons- Shao-Chun Wang

  36. Conclusion • We described a DHL method that address network non-uniformity by using range ratios • improve localization accuracy • lower packet transmission overhead Shao-Chun Wang

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