Location in distributed ad-hoc wireless sensor networks

By Chris Savarese, Jan M. Rabaey, J. Beutel. 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2001

695 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/d60685748b091fcbf4d03abea8425e45299e682f

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Citations in the corpus

Using proximity and quantized RSS for sensor localization in wireless networks (2003, background): “The literature reflects widespread interest in developing the technologies needed to achieve location estimation in wireless sensor networks [1][ 24 ][30][27][8][15] [17][21].”
Locating the nodes: cooperative localization in wireless sensor networks (2005, neutral): “Central Computer Central Computer article, we use “cooperative” localization [ 7 ] to emphasize the communication and measurements between many pairs of sensors required to achieve localization for all sensors.”
Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks (2005, background): “HE emergence of miniature low-power devices that integrate micro-sensing and actuation with on-board processing and wireless communication capabilities has stimulated great interests in developing wireless ad hoc sensor network [1], [ 2 ].”
A Theoretical Foundation of Network Localization and Navigation (2018, neutral): “[129] C.”
Distributed weighted-multidimensional scaling for node localization in sensor networks (2006, methodology): “The devices successively reflne their location estimates [Albowicz et al. 2001; Savarese et al. 2001 ], efiectively flnding a solution to a global optimization problem that uses all ranges measured between neighbors.”
Anchor-Free Distributed Localization in Sensor Networks (2003, methodology): “The Terrain algorithm, another anchor-based algorithm, builds on ABC [21].”
Angle of Arrival Localization for Wireless Sensor Networks (2006, methodology): “In [1]–[3], the RSS, which is the easiest to obtain for the current sensors, is utilized.”
Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks (2002, neutral): “Recently a number of approaches have been proposed that require few anchors [4, 9, 10, 11].”
Distributed algorithms for transmission power control in wireless sensor networks (2003, background): “In recent publications the problem of power control was addressed while assuming information on the angle of reception [8] or the nodes knowledge of its location [9][10].”
A directionality based location discovery scheme for wireless sensor networks (2002, methodology): “Techniques using a combination of RSSI and other measurements may lead to reliable location estimates, as proposed in [2, 3, 15].”
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks (2003, background): “once it is in an activated ’on’ state. This can be done using GPS or sensor localization which is itself an area of active research, and algorithms to achieve this task are described in [5], [3], and [4], among others. Next, each sensor must determine a method of communication with other sensors cov”
The Cricket indoor location system (2005, methodology): “The ABC algorithm is an incremental algorithm that does not use anchor nodes [81].”
Localization Algorithms in Wireless Sensor Networks: Current Approaches and Future Challenges (2010, methodology): “org/npa 59 robust to errors in local distance estimate [13].”
Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling (2004, methodology): “Moreover, cumulative measurement error is a constant problem of some existing sensor positioning methods [10], [20], [25].”
Distributed Sensor Localization in Random Environments Using Minimal Number of Anchor Nodes (2008, methodology): “e sensor networks. A distributed multidimensional scaling algorithm is presented in [15]. Successive reﬁnement algorithms where a cost function minimization is done iteratively are presented in [16], [17], [18]. Reference [16] discusses an iterative scheme where they assume 5% of the nodes as anchor”