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379
RangeFree Localization Schemes for Large Scale Sensor Networks
, 2003
"... Wireless Sensor Networks have been proposed for a multitude of locationdependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of rangebased localization schemes that depend on absolute pointtopoint distance estimates. Because coarse accura ..."
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Cited by 518 (10 self)
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Wireless Sensor Networks have been proposed for a multitude of locationdependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of rangebased localization schemes that depend on absolute pointtopoint distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in rangefree localization are being pursued as a costeffective alternative to more expensive rangebased approaches. In this paper, we present APIT, a novel localization algorithm that is rangefree. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three stateoftheart rangefree localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius.
Robust Distributed Network Localization with Noisy Range Measurements
, 2004
"... This paper describes a distributed, lineartime algorithm for localizing sensor network nodes in the presence of range measurement noise and demonstrates the algorithm on a physical network. We introduce the probabilistic notion of robust quadrilaterals as a way to avoid flip ambiguities that otherw ..."
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Cited by 392 (21 self)
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This paper describes a distributed, lineartime algorithm for localizing sensor network nodes in the presence of range measurement noise and demonstrates the algorithm on a physical network. We introduce the probabilistic notion of robust quadrilaterals as a way to avoid flip ambiguities that otherwise corrupt localization computations. We formulate the localization problem as a twodimensional graph realization problem: given a planar graph with approximately known edge lengths, recover the Euclidean position of each vertex up to a global rotation and translation. This formulation is applicable to the localization of sensor networks in which each node can estimate the distance to each of its neighbors, but no absolute position reference such as GPS or fixed anchor nodes is available. We implemented the algorithm on a physical sensor network and empirically assessed its accuracy and performance. Also, in simulation, we demonstrate that the algorithm scales to large networks and handles realworld deployment geometries. Finally, we show how the algorithm supports localization of mobile nodes.
Distributed Localization in Wireless Sensor Networks: A Quantitative Comparison
, 2003
"... This paper studies the problem of determining the node locations in adhoc sensor networks. We compare three distributed localization algorithms (Adhoc positioning, Robust positioning, and Nhop multilateration) on a single simulation platform. The algorithms share a common, threephase structure: ..."
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Cited by 298 (7 self)
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This paper studies the problem of determining the node locations in adhoc sensor networks. We compare three distributed localization algorithms (Adhoc positioning, Robust positioning, and Nhop multilateration) on a single simulation platform. The algorithms share a common, threephase structure: (1) determine nodeanchor distances, (2) compute node positions, and (3) optionally refine the positions through an iterative procedure. We present a detailed analysis comparing the various alternatives for each phase, as well as a headtohead comparison of the complete algorithms. The main conclusion is that no single algorithm performs best; which algorithm is to be preferred depends on the conditions (range errors, connectivity, anchor fraction, etc.). In each case, however, there is significant room for improving accuracy and/or increasing coverage.
The Bits and Flops of the Nhop Multilateration Primitive For Node Localization Problems
, 2002
"... The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. Vital to the success of wireless microsensor networks is the ability of microsensors to "collectively perform sensi ..."
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Cited by 282 (2 self)
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The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. Vital to the success of wireless microsensor networks is the ability of microsensors to "collectively perform sensing and computation". In this paper, we study one of the fundamental challenges in sensor networks, node localization. The collaborative multilateration presented here, enables adhoc deployed sensor nodes to accurately estimate their locations by using known beacon locations that are several hops away and distance measurements to neighboring nodes. To prevent error accumulation in the network, node locations are computed by setting up and solving a global nonlinear optimization problem. The solution is presented in two computation models, centralized and a fully distributed approximation of the centralized model. Our simulation results show that using the fully distributed model, resource constrained sensor nodes can collectively solve a large nonlinear optimization problem that none of the nodes can solve individually. This approach results in significant savings in computation and communication, that allows finegrained localization to run on a low cost sensor node we have developed.
DV Based Positioning in Ad Hoc Networks
, 2003
"... Many ad hoc network protocols and applications assume the knowledge of geographic location of nodes. The absolute position of each networked node is an assumed fact by most sensor networks which can then present the sensed information on a geographical map. Finding position without the aid of GPS in ..."
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Cited by 238 (4 self)
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Many ad hoc network protocols and applications assume the knowledge of geographic location of nodes. The absolute position of each networked node is an assumed fact by most sensor networks which can then present the sensed information on a geographical map. Finding position without the aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use due to power, form factor or line of sight conditions. Position would also enable routing in sufficiently isotropic large networks, without the use of large routing tables. We are proposing APS  a localized, distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate position for all nodes in a network where only a limited fraction of nodes have self positioning capability.
Semidefinite Programming for Ad Hoc Wireless Sensor Network Localization
, 2004
"... We describe an SDP relaxation based method for the position estimation problem in wireless sensor networks. The optimization problem is set up so as to minimize the error in sensor positions to fit distance measures. Observable gauges are developed to check the quality of the point estimation of sen ..."
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Cited by 225 (14 self)
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We describe an SDP relaxation based method for the position estimation problem in wireless sensor networks. The optimization problem is set up so as to minimize the error in sensor positions to fit distance measures. Observable gauges are developed to check the quality of the point estimation of sensors or to detect erroneous sensors. The performance of this technique is highly satisfactory compared to other techniques. Very few anchor nodes are required to accurately estimate the position of all the unknown nodes in a network. Also the estimation errors are minimal even when the anchor nodes are not suitably placed within the network or the distance measurements are noisy.
Improved MDSbased localization
 In Proceedings of IEEE INFOCOM ’04, Hong Kong
, 2004
"... Abstract — It is often useful to know the geographic positions of nodes in a communications network, but adding GPS receivers or other sophisticated sensors to every node can be expensive. MDSMAP is a recent localization method based on multidimensional scaling (MDS). It uses connectivity informati ..."
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Cited by 180 (1 self)
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Abstract — It is often useful to know the geographic positions of nodes in a communications network, but adding GPS receivers or other sophisticated sensors to every node can be expensive. MDSMAP is a recent localization method based on multidimensional scaling (MDS). It uses connectivity information—who is within communications range of whom—to derive the locations of the nodes in the network, and can take advantage of additional data, such as estimated distances between neighbors or known positions for certain anchor nodes, if they are available. However, MDSMAP is an inherently centralized algorithm and is therefore of limited utility in many applications. In this paper, we present a new variant of the MDSMAP method, which we call MDSMAP(P) standing for MDSMAP using patches of relative maps, that can be executed in a distributed fashion. Using extensive simulations, we show that the new algorithm not only preserves the good performance of the original method on relatively uniform layouts, but also performs much better than the original on irregularlyshaped networks. The main idea is to build a local map at each node of the immediate vicinity and then merge these maps together to form a global map. This approach works much better for topologies in which the shortest path distance between two nodes does not correspond well to their Euclidean distance. We also discuss an optional refinement step that improves solution quality even further at the expense of additional computation. I.
Sensor Positioning in Wireless Adhoc Sensor Networks Using Multidimensional Scaling
, 2004
"... Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. In the paper, we first study some situations where most existing sensor positioning methods tend to fail to perform well, an example being when the topology of a sensor network is anisotropic. Then, we ..."
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Cited by 150 (0 self)
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Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. In the paper, we first study some situations where most existing sensor positioning methods tend to fail to perform well, an example being when the topology of a sensor network is anisotropic. Then, we explore the idea of using dimensionality reduction techniques to estimate sensors coordinates in two (or three) dimensional space, and we propose a distributed sensor positioning method based on multidimensional scaling technique to deal with these challenging conditions. Multidimensional scaling and coordinate alignment techniques are applied to recover positions of adjacent sensors. The estimated positions of the anchors are compared with their true physical positions and corrected, The positions of other sensors are corrected accordingly. With iterative adjustment, our method can overcome adverse network and terrain conditions, and generate accurate sensor position. We also propose an on demand sensor positioning method based on the above method.
Robust statistical methods for securing wireless localization in sensor networks
 In Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks (IPSN
, 2005
"... Abstract — Many sensor applications are being developed that require the location of wireless devices, and localization schemes have been developed to meet this need. However, as locationbased services become more prevalent, the localization infrastructure will become the target of malicious attack ..."
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Cited by 129 (4 self)
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Abstract — Many sensor applications are being developed that require the location of wireless devices, and localization schemes have been developed to meet this need. However, as locationbased services become more prevalent, the localization infrastructure will become the target of malicious attacks. These attacks will not be conventional security threats, but rather threats that adversely affect the ability of localization schemes to provide trustworthy location information. This paper identifies a list of attacks that are unique to localization algorithms. Since these attacks are diverse in nature, and there may be many unforseen attacks that can bypass traditional security countermeasures, it is desirable to alter the underlying localization algorithms to be robust to intentionally corrupted measurements. In this paper, we develop robust statistical methods to make localization attacktolerant. We examine two broad classes of localization: triangulation and RFbased fingerprinting methods. For triangulationbased localization, we propose an adaptive least squares and least median squares position estimator that has the computational advantages of least squares in the absence of attacks and is capable of switching to a robust mode when being attacked. We introduce robustness to fingerprinting localization through the use of a medianbased distance metric. Finally, we evaluate our robust localization schemes under different threat conditions. I.
AnchorFree Distributed Localization in Sensor Networks
, 2003
"... Many sensor network applications require that each node's sensor stream be annotated with its physical location in some common coordinate system. Manual measurement and configuration methods for obtaining location don't scale and are errorprone, and equipping sensors with GPS is often exp ..."
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Cited by 126 (8 self)
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Many sensor network applications require that each node's sensor stream be annotated with its physical location in some common coordinate system. Manual measurement and configuration methods for obtaining location don't scale and are errorprone, and equipping sensors with GPS is often expensive and does not work in indoor and urban deployments. Sensor networks can therefore benefit from a selfconfiguring method where nodes cooperate with each other, estimate local distances to their neighbors, and converge to a consistent coordinate assignment. This paper describes a fully decentralized algorithm called AFL (AnchorFree Localization) where nodes start from a random initial coordinate assignment and converge to a consistent solution using only local node interactions. The key idea in AFL is foldfreedom, where nodes first configure into a topology that resembles a scaled and unfolded version of the true configuration, and then run a forcebased relaxation procedure.We show using extensive simulations under a variety of network sizes, node densities, and distance estimation errors that our algorithm is superior to previously proposed methods that incrementally compute the coordinates of nodes in the network, in terms of its ability to compute correct coordinates under a wider variety of conditions and its robustness to measurement errors.