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Issue No.03 - March (2011 vol.10)

pp: 335-348

Zhong Zhou , University of Connecticut, Storrs

Zheng Peng , University of Connecticut, Storrs

Jun-Hong Cui , University of Connecticut, Storrs

Zhijie Shi , University of Connecticut , Storrs

Amvrossios C. Bagtzoglou , University of Connecticut, Storrrs

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2010.158

ABSTRACT

Due to harsh aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on the predicted mobility pattern. Anchor nodes with known locations in the network will control the localization process in order to balance the trade-off between localization accuracy, localization coverage, and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

INDEX TERMS

Network architecture and design, network communications, network protocols, applications, miscellaneous, localization, underwater sensor networks.

CITATION

Zhong Zhou, Zheng Peng, Jun-Hong Cui, Zhijie Shi, Amvrossios C. Bagtzoglou, "Scalable Localization with Mobility Prediction for Underwater Sensor Networks",

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