The mission-oriented self-deploying methods for wireless mobile sensor networks
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Pervasive and Mobile Computing
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Sensor deployment is a key issue in target detection. While a lot of works have been done to achieve "physical coverage'', few work addresses meeting high detection accuracy presented as a specific high detection probability and a low false alarm rate. In this paper, we employ a data-fusion based collaborative detection scheme for achieving guaranteed accuracy in sensor deployment. A "density first'' clustering algorithm is adopt to organize preselected surveillance locations into deployment units, place sensors to cover these locations from the intensive region to sparse one. The simulation results show that our deployment algorithm can significantly reduce total number of deployed sensors with guaranteed accuracy compare with the previous works.