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Wireless Sensor Network Localization Techniques
"... Wireless sensor network localization is an important area that attracted significant research interest. This interest is expected to grow further with the proliferation of wireless sensor network applications. This paper provides an overview of the measurement techniques in sensor network localizat ..."
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Cited by 209 (5 self)
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Wireless sensor network localization is an important area that attracted significant research interest. This interest is expected to grow further with the proliferation of wireless sensor network applications. This paper provides an overview of the measurement techniques in sensor network localization and the onehop localization algorithms based on these measurements. A detailed investigation on multihop connectivitybased and distancebased localization algorithms are presented. A list of open research problems in the area of distancebased sensor network localization is provided with discussion on possible approaches to them.
Rendered Path: RangeFree Localization in Anisotropic Sensor Networks with Holes
, 2007
"... Sensor positioning is a crucial part of many locationdependent applications that utilize wireless sensor networks (WSNs). Current localization approaches can be divided into two groups: rangebased and rangefree. Due to the high costs and critical assumptions, the rangebased schemes are often imp ..."
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Cited by 85 (14 self)
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Sensor positioning is a crucial part of many locationdependent applications that utilize wireless sensor networks (WSNs). Current localization approaches can be divided into two groups: rangebased and rangefree. Due to the high costs and critical assumptions, the rangebased schemes are often impractical for WSNs. The existing rangefree schemes, on the other hand, suffer from poor accuracy and low scalability. Without the help of a large number of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose the Rendered Path (REP) protocol. To the best of our knowledge, REP is the only rangefree protocol for locating sensors with constant number of seeds in anisotropic sensor networks.
Beyond Trilateration: On the Localizability of Wireless Adhoc Networks
"... Abstract — The proliferation of wireless and mobile devices has fostered the demand of context aware applications, in which location is often viewed as one of the most significant contexts. Classically, trilateration is widely employed for testing network localizability; even in many cases it wrongl ..."
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Cited by 42 (12 self)
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Abstract — The proliferation of wireless and mobile devices has fostered the demand of context aware applications, in which location is often viewed as one of the most significant contexts. Classically, trilateration is widely employed for testing network localizability; even in many cases it wrongly recognizes a localizable graph as nonlocalizable. In this study, we analyze the limitation of trilateration based approaches and propose a novel approach which inherits the simplicity and efficiency of trilateration, while at the same time improves the performance by identifying more localizable nodes. We prove the correctness and optimality of this design by showing that it is able to locally recognize all 1hop localizable nodes. To validate this approach, a prototype system with 19 wireless sensors is deployed. Intensive and largescale simulations are further conducted to evaluate the scalability and efficiency of our design. I.
Underwater Localization in Sparse 3D Acoustic Sensor Networks
 in Proceedings of INFOCOM
, 2008
"... Abstract—We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its twodimensional counterpart via a projection technique and prove t ..."
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Cited by 39 (3 self)
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Abstract—We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its twodimensional counterpart via a projection technique and prove that a nondegenerative projection preserves network localizability. We further prove that given a network and a constant k, all of the geometric klateration localization methods are equivalent. Based on these results, we design a purely distributed localization framework termed USP. This framework can be applied with any ranging method proposed for 2D terrestrial sensor networks. Through theoretical analysis and extensive simulation, we show that USP preserves the localizability of the original 3D network via a simple projection and improves localization capabilities when bilateration is employed. USP has low storage and computation requirements, and predictable and balanced communication overhead. Index Terms—3D underwater localization, acoustic sensor networks, network localization problem, localizability. I.
Sea Depth Measurement with Restricted Floating Sensors
, 2007
"... Sea depth monitoring is a critical task to ensure the safe operation of harbors. Traditional schemes largely rely on laborintensive work and expensive hardware. This study explores the possibility of deploying networked sensors on the surface of sea, measuring and reporting sea depth of given areas ..."
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Cited by 35 (14 self)
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Sea depth monitoring is a critical task to ensure the safe operation of harbors. Traditional schemes largely rely on laborintensive work and expensive hardware. This study explores the possibility of deploying networked sensors on the surface of sea, measuring and reporting sea depth of given areas. We propose a Restricted Floating Sensors (RFS) model, in which sensor nodes are anchored to the sea bottom, floating within a restricted area. Distinguished from traditional stationary or mobile sensor networks, the RFS network consists of sensor nodes with restricted mobility. We construct the network model and elaborate the corresponding localization problem. We show that by locating such RFS sensors, the sea depth can be estimated without the help of any extra ranging devices. A prototype system with 25 Telos sensor nodes is deployed to validate this design. We also examine the efficiency and scalability of this design through largescale simulations.
Connectivitybased Localization of Large Scale Sensor Networks with Complex Shape
"... Abstract—We study the problem of localizing a large sensor network having a complex shape, possibly with holes. A major challenge with respect to such networks is to figure out the correct network layout, i.e., avoid global flips where a part of the network folds on top of another. Our algorithm fir ..."
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Cited by 32 (4 self)
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Abstract—We study the problem of localizing a large sensor network having a complex shape, possibly with holes. A major challenge with respect to such networks is to figure out the correct network layout, i.e., avoid global flips where a part of the network folds on top of another. Our algorithm first selects landmarks on network boundaries with sufficient density, then constructs the landmark Voronoi diagram and its dual combinatorial Delaunay complex on these landmarks. The key insight is that the combinatorial Delaunay complex is provably globally rigid and has a unique realization in the plane. Thus an embedding of the landmarks by simply gluing the Delaunay triangles properly recovers the faithful network layout. With the landmarks nicely localized, the rest of the nodes can easily localize themselves by trilateration to nearby landmark nodes. This leads to a practical and accurate localization algorithm for large networks using only network connectivity. Simulations on various network topologies show surprisingly good results. In comparison, previous connectivitybased localization algorithms such as multidimensional scaling and rubberband representation generate globally flipped or distorted localization results. I.
Quality of trilateration: confidencebased iterative localization,”
 IEEE Transactions on Parallel and Distributed Systems,
, 2010
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Localization with SnapInducing Shaped Residuals (SISR): Coping with Errors
 in Measurement,” in The 15th Annual International Conference on Mobile Computing and Networking
, 2009
"... We consider the problem of localizing wireless nodes in an outdoor, openspace environment, using adhoc radio ranging measurements, e.g., 802.11. We cast these ranging measurements as a set of distance constraints, thus forming an overdetermined system of equations suitable for nonlinear least sq ..."
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Cited by 17 (4 self)
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We consider the problem of localizing wireless nodes in an outdoor, openspace environment, using adhoc radio ranging measurements, e.g., 802.11. We cast these ranging measurements as a set of distance constraints, thus forming an overdetermined system of equations suitable for nonlinear least squares optimization. However, ranging measurements are often subject to errors, induced by multipath signals and variations in path loss, unreliable hardware or antenna connectors, or imperfection in measurement models. Such potentially large, nonGaussian errors in the measurement data ultimately produce inaccurate localization solutions. We propose a new errortolerant localization method, called snapinducing shaped residuals (SISR), to identify automatically “bad nodes ” and “bad links ” arising from these errors, so that they receive less weight in the localization process. In particular, SISR snaps “good nodes ” to their accurate locations and gives less emphasis to other nodes. While the mathematical techniques used by SISR are similar to robust statistics, SISR’s exploitation of the snapin effect in localization appears to be novel. We provide analysis on the principle of SISR, illustrate errors in realworld measurements, and demonstrate a working SISR implementation in field experiments on a testbed of 37 wireless nodes, as well as show the superior performance of SISR in simulation with a larger number of nodes.
Quality of Trilateration: Confidence based Iterative Localization
 In Proceedings of the 28th International Conference on Distributed Computing Systems
, 2008
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