A Theory of Network Localization

Aspnes, James; Eren, Tolga; Goldenberg, David K.; Morse, A. Stephen; Whiteley, Walter; Yang, Yufan; Anderson, Brian D. O.; Belhumeur, Peter N.

doi:10.1109/tmc.2006.174

Cited by 563 publications

(409 citation statements)

References 64 publications

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“…In molecular conformation (see, e.g., [9,26]), solving the GRP in dimension three allows construction of the 3-dimensional structure of the molecule. In wireless sensor network localization (see, e.g., [6,16]), where one is interested in inferring the locations of sensor nodes in a sensor network. And in computer vision, where image reconstruction is performed from selected pairwise distances of labeled sources [8,25].…”

Section: Introductionmentioning

confidence: 99%

Constructing Uniquely Realizable Graphs

Pak¹,

Vilenchik

2013

Discrete Comput Geom

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In the Graph Realization Problem (GRP), one is given a graph G, a set of non-negative edge-weights, and an integer Theory, combined with an explicit construction and algebraic calculations of the rigidity (stress) matrix. As an application of our results, we describe a general framework to construct uniquely k-colorable graphs. These graphs have the extra property of being uniquely vector k-colorable. We give a deterministic explicit construction of such a family using Cayley expander graphs.

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Section: Introductionmentioning

confidence: 99%

Constructing Uniquely Realizable Graphs

Pak¹,

Vilenchik

2013

Discrete Comput Geom

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“…A graph is a trilateration extension if it has a trilateration ordering. It is shown that trilateration extensions are globally rigid [69,76] .…”

Section: Trilaterationmentioning

confidence: 99%

Location, Localization, and Localizability

Liu

Yang

Wang

et al. 2010

J. Comput. Sci. Technol.

268

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Location-aware technology spawns numerous unforeseen pervasive applications in a wide range of living, production, commence, and public services. This article provides an overview of the location, localization, and localizability issues of wireless ad-hoc and sensor networks. Making data geographically meaningful, location information is essential for many applications, and it deeply aids a number of network functions, such as network routing, topology control, coverage, boundary detection, clustering, etc. We investigate a large body of existing localization approaches with focuses on error control and network localizability, the two rising aspects that attract significant research interests in recent years. Error control aims to alleviate the negative impact of noisy ranging measurement and the error accumulation effect during cooperative localization process. Network localizability provides theoretical analysis on the performance of localization approaches, providing guidance on network configuration and adjustment. We emphasize the basic principles of localization to understand the state-of-the-art and to address directions of future research in the new and largely open areas of location-aware technologies.Keywords location-based services (LBS), localization, error control, localizability, wireless ad-hoc and sensor networks LocationThe proliferation of wireless and mobile devices has fostered the demand for context-aware applications, in which location is viewed as one of the most significant contexts. For example, pervasive medical care is designed to accurately record and manage patient movements [1][2] ; smart space enables the interaction between physical space and human activities [3][4] ; modern logistics has major concerns on goods transportation, inventory, and warehousing [5][6] ; environmental monitoring networks sense air, water, and soil quality and detect the source of pollutants in real time [7][8][9][10][11] ; and mobile peer-to-peer computing encourages content sharing and contributing among mobile hosts in the vicinity [12][13] . In brief, location-based service (LBS) is a key enabling technology of these applications and widely exists in nowadays wireless communication networks from the short-range Bluetooth to the long-range telecommunication networks, as illustrated in Fig.1.Recent technological advances have enabled the development of low-cost, low-power, and multifunctional sensor devices. These nodes are autonomous devices with integrated sensing, processing, and communication capabilities. With the rapid development of wireless sensor networks (WSNs), location information becomes critically essential and indispensable. The overwhelming reason is that WSNs are fundamentally intended to provide information on spatial-temporal characteristics of the physical world; hence, it is important to associate sensed data with locations, making data geographically meaningful. For example, a number of applications, such as object tracking and environment monitoring, inherently rely on loc...

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“…Since our graph matching cannot localize sensors correctly, due to the topology symmetricity, we need anchor nodes that are sensors with GPS receivers. We need to determine whether we can localize sensors uniquely by testing the conditions for unique localizability discussed in [1]. If there is a topology symmetricity in the road network, we need to find out a minimum number of anchor nodes and the places to remove the ambiguity for graph matching before applying our localization scheme to the road network.…”

Section: Matching Ambiguity Due To Topology Symmetricitymentioning

confidence: 99%

APL: Autonomous Passive Localization for Wireless Sensors Deployed in Road Networks

Jeong¹,

Guo²,

He³

et al. 2008

2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications

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In road networks, sensor nodes are deployed sparsely (hundreds of meters apart) to save costs. This makes the existing localization solutions based on the ranging ineffective. To address this issue, this paper introduces an autonomous passive localization scheme, called APL. Our work is inspired by the fact that vehicles move along routes with a known map. Using vehicle-detection timestamps, we can obtain distance estimates between any pair of sensors on roadways to construct a virtual graph composed of sensor identifications (i.e., vertices) and distance estimates (i.e., edges). The virtual graph is then matched with the topology of road map, in order to identify where sensors are located in roadways. We evaluate our design in local roadway and show that our distance estimate method works well. In addition, we show that our localization scheme is effective in a road network with eighteen intersections, where we found no location matching error, even with a maximum sensor time synchronization error of 0.3[sec] and the vehicle speed deviation of 10[km/h].

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A Theory of Network Localization

Cited by 563 publications

References 64 publications

Constructing Uniquely Realizable Graphs

Constructing Uniquely Realizable Graphs

Location, Localization, and Localizability

APL: Autonomous Passive Localization for Wireless Sensors Deployed in Road Networks

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