Localization for mobile sensor networks

By Lingxuan Hu, David E. Evans. ACM/IEEE International Conference on Mobile Computing and Networking, 2004

1,182 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/63bf17e4f0a0137d5eea3bffb0f5f953914e068d

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In Computer Networks and Communications

In Electrical and Electronic Engineering

In Ocean Engineering

Citations in the corpus

Scalable Localization with Mobility Prediction for Underwater Sensor Networks (2008, background): “Localization for terrestrial mobile sensor networks has also been explored recently [17], [32].”
Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning (2007, background): “Hu & Evans 2004 ) to smooth the trajectory and enhance the performance of localization.”
Distributed Sensor Localization in Random Environments Using Minimal Number of Anchor Nodes (2008, methodology): “Sequential Monte Carlo methods for mobile localization are considered in [22].”
A survey on sensor localization (2010, methodology): “Monte Carlo localization (MCL) method was adopted in [ 35 ] to solve the localization problem in a mobile sensor network.”
Movement-assisted sensor deployment (2004, neutral): “Hu et al. [ 14 ] have provided detailed discussion of these techniques.”
Algorithms and Protocols for Wireless Sensor Networks (2008, methodology): “The location problem consists in finding the geographic location of the nodes in aWSN,which can be computed by a central unit [2] or by sensor nodes in a distributedmanner [3–8].”
Localization algorithms of Wireless Sensor Networks: a survey (2011, methodology): “The detailed information of typical algorithms [2, 15, 33] is described in the sequel.”
Localization in Wireless Sensor Networks (2007, methodology): “Our work is inspired by Hu and Evans [14], who proposed a range-free algorithm, MCL (Monte Carlo Localization), that only works in mobile sensor networks.”
Locating the nodes: cooperative localization in wireless sensor networks (2005, background): “, candidate representations of its coordinates, weighted according to their likelihood [76], [77].”
A Survey on Localization for Mobile Wireless Sensor Networks (2009, methodology): “A widely used localization technique for mobile robots is dead reckoning [3], [64], [65], [7].”