Yi Zou
Krishnendu Chakrabarty
Abstract
The effectiveness of cluster-based distributed sensor networks depends to a large extent on the coverage provided by the sensor deployment. We propose a virtual force algorithm (VFA) as a sensor deployment strategy to enhance the coverage after an initial random placement of sensors. For a given number of sensors, the VFA algorithm attempts to maximize the sensor field coverage. A judicious combination of attractive and repulsive forces is used to determine the new sensor locations that improve the coverage. Once the effective sensor positions are identified, a one-time movement with energy consideration incorporated is carried out, that is, the sensors are redeployed, to these positions. We also propose a novel probabilistic target localization algorithm that is executed by the cluster head. The localization results are used by the cluster head to query only a few sensors (out of those that report the presence of a target) for more detailed information. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
- Bhardwaj, M. and Chandrakasan, A. P. 2002. Bounding the lifetime of sensor networks via optimal role assignments. In Proceedings of IEEE INFOCOM, 1587--1596.Google Scholar
- Brooks, R. R. and Iyengar, S. S. 1997. Multi-Sensor Fusion: Fundamentals and Applications with Software. Prentice Hall, Upper Saddle River, NJ. Google ScholarDigital Library
- Bulusu, N., Heidemann, J., and Estrin, D. 2001. Adaptive beacon placement. In Proceedings of the International Conference on Distributed Computing Systems, 489--498. Google ScholarDigital Library
- Chakrabarty, K., Iyengar, S. S., Qi, H., and Cho, E. 2001. Coding theory framework for target location in distributed sensor networks. In Proceedings of the International Symposium on Information Technology: Coding and Computing, 130--134. Google ScholarDigital Library
- Chakrabarty, K., Iyengar, S. S., Qi, H., and Cho, E. 2002. Grid coverage for surveillance and target location in distributed sensor networks. IEEE Trans. Comput. 51, 1448--1453. Google ScholarDigital Library
- Dhillon, S. S., Chakrabarty, K., and Iyengar, S. S. 2002. Sensor placement algorithms for grid coverage. In Proceedings of the International Conference on Information Fusion, 1581--1587.Google Scholar
- Elfes, A. 1990. Occupancy grids: A stochastic spatial representation for active robot perception. In Proceedings of the 6th Conference on Uncertainty in AI, 60--70.Google Scholar
- Heidemann, J. and Bulusu, N. 2001. Using geospatial information in sensor networks. In Proceedings of CSTB Workshop on Intersection of Geospatial Information and Information Technology.Google Scholar
- Howard, A., Matarić, M. J., and Sukhatme, G. S. 2002. Mobile sensor network deployment using potential field: A distributed scalable solution to the area coverage problem. In Distributed Autonomous Robotic Systems 5: Proceedings of the 6th International Conference on Distributed Autonomous Robotic Systems (DARS02), 299--308.Google Scholar
- Iyengar, S. S., Prasad, L., and Min, H. 1995. Advances in Distributed Sensor Technology. Prentice Hall, Englewood Cliffs, NJ. Google ScholarDigital Library
- Kasetkasem, T. and Varshney, P. K. 2001. Communication structure planning for multisensor detection systems. In IEE Proceedings of Radar, Sonar and Navigation. Vol. 148, 2--8.Google ScholarCross Ref
- Locateli, M. and Raber, U. 2002. Packing equal circles in a square: a deterministic global optimization approach. Discrete Appl. Math. 122, 139--166. Google ScholarDigital Library
- Meguerdichian, S., Slijepcevic, S., Karayan, V., and Potkonjak, M. 2001. Coverage problems in wireless ad-hoc sensor networks. In Proceedings of IEEE INFOCOM. Vol. 3, 1380--1387.Google Scholar
- Musman, S. A., Lehner, P. E., and Elsaesser, C. 1997. Sensor planning for elusive targets. J. Computer & Mathematical Modeling 25, 103--115. Google ScholarDigital Library
- O'Rourke, J. 1987. Art Gallery Theorems and Algorithms. Oxford University Press, New York. Google ScholarDigital Library
- Penny, D. E. 1998. The automatic management of multi-sensor systems. In Proceedings of the International Conference on Information Fusion.Google Scholar
- Priyantha, N. B., Chakraborty, A., and Balakrishnan, H. 2000. The cricket location-support system. In Proceedings of ACM/IEEE International Conference on Mobile Computing and Networking. 32--43. Google ScholarDigital Library
- Qi, H., Iyengar, S. S., and Chakrabarty, K. 2001. Multi-resolution data integration using mobile agents in distributed sensor networks. IEEE Trans. System, Man and Cybernetics 31, 383--391. Google ScholarDigital Library
- Rappaport, T. S. 1996. Wireless Communications: Principles and Practice. Prentice Hall, Upper Saddle River, NJ. Google ScholarDigital Library
- Varshney, P. K. 1996. Distributed Detection and Data Fusion. Springer, New York. Google ScholarDigital Library
- Zou, Y. and Chakrabarty, K. 2003. Sensor deployment and target localization based on virtual forces. In Proceedings of IEEE INFOCOM.Google Scholar
Index Terms
- Sensor deployment and target localization in distributed sensor networks
Recommendations
Uncertainty-aware and coverage-oriented deployment for sensor networks
We consider the sensor deployment problem in the context of uncertainty in sensor locations subsequent to airdropping. Sensor deployment in such scenarios is inherently non-deterministic and there is a certain degree of randomness associated with the ...
An Energy Efficient Clustering Approach in Wireless Sensor Networks
ICCSEE '12: Proceedings of the 2012 International Conference on Computer Science and Electronics Engineering - Volume 01A wireless sensor network (WSN) consists of a large number of low-power micro-sensors. The data collected by each sensor is communicated through the network to a single sink node. Data gathering is a key work of the wireless sensor network. To prolong ...
Dynamic deployment of randomly deployed mobile sensor nodes in the presence of obstacles
For random deployment of wireless sensor networks in a specified geographical location and in the presence of obstacles, optimal network coverage is highly desirable while maintaining network connectivity. In this piece of work, we propose an efficient ...
Reviews
Joao Orvalho
The effectiveness of cluster-based distributed sensor networks depends, to a large extent, on the coverage provided by the sensor deployment, as the authors of this paper state. They propose a virtual force algorithm (VFA) as a sensor deployment strategy, to enhance coverage after an initial random placement of sensors. The paper is very well written, and is technically sound. It stimulates discussion, especially the simulation results. The authors demonstrate how a probabilistic localization algorithm can be used in combination with force-directed sensor placement, and, also, can reduce the energy consumption needed for target detection and location, which is a challenging set of issues in itself. Online Computing Reviews Service
Access critical reviews of Computing literature here
Become a reviewer for Computing Reviews.
Comments