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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 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
Outline • Introduction • Background and Related Work • Density-Aware Hop-Count Localization (DHL) • Simulation Result • Conclusion Shao-Chun Wang
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
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
Introduction • Goal • improve the accuracy of location estimation when the node distribution is non-uniform Shao-Chun Wang
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
Background and Related Work-(cont.)- • Case A Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang
Background and Related Work-(cont.)- • Case B Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang
Background and Related Work-(cont.)- • Case C Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang
Background and Related Work-(cont.)- • Case D Reference Node Forwarding Node Destination Node Node Transmission Range : R Shao-Chun Wang
R 2R 3R 4R Background and Related Work-(cont.)- Case D Case C Case B Case A Actual Distance Estimated Distance Shao-Chun Wang
Background and Related Work-(cont.)- • “Ad hoc positioning system (APS)” • Globecom 2001 • DV-Hop
Background and Related Work-(cont.)- • DV-Hop R1,R2,R3:Refernece Node 1.Flooding Beacon: Location Information R2 R3 A R1 Shao-Chun Wang
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 }
Background and Related Work-(cont.)- • DV-Hop 3.Reference Node estimates an average size for one hop R2 75m 40m R3 A R1 100m
Background and Related Work-(cont.)- • DV-Hop 4.Flooding Beacon: Average size for one hop R2 R3 A R1 Shao-Chun Wang
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
Background and Related Work • The distance per hop is greater in dense regions and smaller in sparse regions Shao-Chun Wang
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
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
Density-Aware Hop-Count Localization-(cont.)- • Density categories • p < Nngbr < q Shao-Chun Wang
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
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
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
Density-Aware Hop-Count Localization-(cont.)- • Hop information update method Shao-Chun Wang
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
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
Simulation Results • Range ratio determination • Distance accuracy comparisons • Position accuracy comparisons • Overhead comparisons Shao-Chun Wang
Simulation Results-Range Ratio Determination (cont.)- • 50m x 50m square area • Transmission range : 5m • Ratio range : 0.1 – 0.9 Shao-Chun Wang
Simulation Results-Range Ratio Determination (cont.)- Shao-Chun Wang
Simulation Results-Range Ratio Determination- Shao-Chun Wang
Simulation Results-Distance Accuracy Comparisons- Shao-Chun Wang
Simulation Results-Position Accuracy Comparisons- Shao-Chun Wang
Simulation Results-Overhead Comparisons (cont.)- Shao-Chun Wang
Simulation Results-Overhead Comparisons- Shao-Chun Wang
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