Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network
By Radhika Nagpal, Howard Elliot Shrobe, Jonathan Bachrach. International Symposium on Information Processing in Sensor Networks, 2003
849 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/d8ea3f18d2f18a69ad774f1ac7cb34ce573d7067
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In Computer Networks and Communications
In Electrical and Electronic Engineering
- Baris Fidan
- Guoqiang Mao
- Yunhao Liu
- Zheng Yang
- David E. Evans
- Lingxuan Hu
- Bodhi Priyantha
- Jennifer C. Hou
Citations in the corpus
- Wireless sensor network localization techniques (2007, background): “[98] more recently can be classified into the same category as the above three algorithms.”
- Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs (2005, methodology): “Using hop-count as an estimate of Euclidian distance (by computing the average distance between sensors in [27] or by analytically deriving it in [32]), a sensor can estimate its position via triangulation.”
- SeRLoc: secure range-independent localization for wireless sensor networks (2004, background): “[25] B. Hofmann-Wellenhof, H. Lichtenegger and J. Collins, Global Positioning System: Theory and Practice, Fourth Edition, Springer-Verlag, 1997.”
- Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms (2004, neutral): “[24, 25], some use triangulation/trigonometry, e.”
- Using Directional Antennas to Prevent Wormhole Attacks (2004, methodology): “In this paper, we consider devices with directional antennas.”
- Scalable Localization with Mobility Prediction for Underwater Sensor Networks (2008, background): “2.2 Related Work on Localization Localization for terrestrial sensor networks has been widely explored, and a significant number of schemes have been proposed [29], [30], [31], [32], [33], [ 34 ], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44].”
- Localization in Wireless Sensor Networks (2007, methodology): “[20] have claimed that rπ/4nd is a lower bound for the error in any range-free localization algorithm in static sensor networks where the nodes only use the connectivity information of the seeds within their first-hop neighborhood.”
- J-Sim: a simulation and emulation environment for wireless sensor networks (2006, methodology): “A common assumption made in most of the methods is that a small portion of sensor nodes (called beacon nodes) are aware of their positions by means of manual configuration or using GPS [27], [47], [54], [46], [30].”
- Location, Localization, and Localizability (2010, background): “Nagpal et al.([38]) demonstrate by algorithm that even better hop-count distance estimates can be computed by averaging distances with neighbors.”
- Distributed Sensor Localization in Random Environments Using Minimal Number of Anchor Nodes (2008, background): “In multilateration algorithms [12]–[15], each sensor estimates its range from the anchors and then calculates its location via multilateration [16].”
- Mobile-assisted localization in wireless sensor networks (2005, background): “Although some previous work also compute node coordinates using connectivity information [27], [4], [28], AFL’s initialization phase is unique in attempting to compute a coordinate assignment that results in a scaled-up unfolded version of the original graph.”
- Robust distributed network localization with noisy range measurements (2004, methodology): “Other techniques use distributed propagation of location information using multilateration [11, 19].”
- Attack-resistant location estimation in sensor networks (2005, methodology): “, [2], [5], [9 ], [18]– [21], [26], [27]) have been proposed for wireless sensor net works in recent years.”
- Anchor-Free Distributed Localization in Sensor Networks (2003, methodology): “A related algorithm for localizing nodes in an ad hoc network uses hop-count and radio strength as distance measures, but assumes nearly uniform node density and no occlusion [18].”
- Range-free localization schemes for large scale sensor networks (2003, background): “Nath • Amorphous Scheme [22] [23] by R.”