Double Mobility: Coverage of the Sea Surface with Mobile Sensor Networks

We are interested in the sensor networks for scientific applications to cover and measure statistics on the sea surface. Due to flows and waves, the sensor nodes may gradually lose their positions; leaving the points of interest uncovered. Manual readjustment is costly and cannot be performed in time. We argue that a network of mobile sensor nodes which can perform self-adjustment is the best candidate to maintain the coverage of the surface area. A key observation of our scheme is that the motion of the flows is not only a curse but should also be considered as a fortune. The sensor nodes can be pushed by free to some locations that potentially improve the overall coverage. To this end, we present a dominating set maintenance scheme to maximally exploit the uncontrollable mobility and balance the energy consumption among all the sensor nodes. We proved that the coverage is guaranteed in our scheme. The simulation demonstrates that the network lifetime can be significantly extended, compared to a straight forward back-to-original reposition scheme.

[1]  Matt Welsh,et al.  Fidelity and yield in a volcano monitoring sensor network , 2006, OSDI '06.

[2]  Anish Arora,et al.  Barrier coverage with wireless sensors , 2005, MobiCom '05.

[3]  Mario Gerla,et al.  The Meandering Current Mobility Model and its Impact on Underwater Mobile Sensor Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[4]  Peter I. Corke,et al.  A Hybrid AUV Design for Shallow Water Reef Navigation , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[5]  Donald F. Towsley,et al.  Mobility improves coverage of sensor networks , 2005, MobiHoc '05.

[6]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[7]  Sukun Kim,et al.  Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[8]  Joseph Pedlosky,et al.  Ocean Circulation Theory , 1996 .

[9]  Nicholas J. Carino,et al.  Health monitoring of civil infrastructures , 2003 .

[10]  Nicholas J. Carino,et al.  Health monitoring of civil infrastructures , 2001, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[11]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[12]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .

[13]  Qian Zhang,et al.  Partial Network Coding: Theory and Application for Continuous Sensor Data Collection , 2006, 200614th IEEE International Workshop on Quality of Service.

[14]  Dan Wang,et al.  Double Mobility: Coverage of the Sea Surface with Mobile Sensor Networks , 2009, INFOCOM.

[15]  Qian Zhang,et al.  Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors , 2007, 2007 Fifteenth IEEE International Workshop on Quality of Service.

[16]  József Balogh,et al.  On k−coverage in a mostly sleeping sensor network , 2008, Wirel. Networks.

[17]  Xiaojiang Du,et al.  Improving sensor network performance by deploying mobile sensors , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[18]  Signell,et al.  Modeling Waves and Circulation in Lake Pontchartrain : ABSTRACT , 1997 .

[19]  Gaurav S. Sukhatme,et al.  Robomote: a tiny mobile robot platform for large-scale ad-hoc sensor networks , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).