A Sweeper Scheme for Localization and Mobility Prediction in Underwater Acoustic Sensor Networks K. T. DharanC. Srimathi*Soo-Hyun Park VIT University Vellore, India *School of Business IT, Kookmin University, Seoul, South Korea IEEE OCEANS 2010

Outline Introduction System model Scheme operation Simulation Conclusion

Introduction Over 71% of the surface is covered by the ocean

Introduction Aquatic applications – Oceanographic data collection – Pollution monitoring – Offshore exploration – Disaster prevention – Assisted navigation – Tactical surveillance applications

Introduction Underwater acoustic sensor networks – More energy-consuming – Long propagation delay – Low bandwidth – Dynamic topology

Introduction Only limited number of schemes have been proposed for the localization service – Small-scale networks – Sensors are static

Goal Devise a scheme for localization and mobility prediction – Large-scale – With good energy efficient – Keep track of the sensor nodes in regular intervals

System model A central node – Adaptive antenna array A large number of sensor nodes – Sensing and transmit data Mobility pattern – Uniform Circular movement – Movement of a node is closely related to neighbor

Scheme operation Central node broadcasts Wakeup message

Scheme operation Sensor nodes check for the current position and reply – Center coordination information – velocity components on each axis

Scheme operation Prediction calculation center position A

Scheme operation Prediction calculation center position A Line A Line B New position Line C position P

Scheme operation Prediction calculation center position A New position position P r radian

Scheme operation Prediction calculation – Distance between point p and center –

Scheme operation Position at a time t k+1

Scheme operation Original coordinate system

Simulation Monte Carlo simulation – The inputs are randomly generated from probability distributions – Rely on repeated random sampling

Simulation

Conclusion The authors proposed a sectored sweeping scheme and mobility prediction scheme – Keep track of the position of the sensor nodes at regular intervals – Energy is saved – Dynamic networks with good energy efficiency The performance of the algorithm is fair

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