NDLI: Recursive Online EM Algorithm for Adaptive Sensor Deployment and Boundary Estimation in Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Zhen Guo MengChu Zhou Guofei Jiang
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ (Zhen Guo; MengChu Zhou)
Abstract	More and more sensor networks are required to monitor and track a large number of objects. Since the topology of mass objects is often dynamic in the real world, their boundary estimation and sensor deployment should be conducted in an adaptive manner. The "current" locations of objects detected by sensors are deemed as new observations into stochastic learning process through recursive distributed EM (expectation-maximization) algorithm. This paper first builds a probabilistic Gaussian mixture model to estimate the mixture distribution of objects locations and then proposes a novel methodology to optimize the sensor deployment and estimate the boundary of objects locations dynamically
Sponsorship	IEEE SYSTEMS, MAN AND CYBERNETICS SOC
Starting Page	862
Ending Page	867
File Size	968205
Page Count	6
File Format	PDF
ISBN	1424400651
DOI	10.1109/ICNSC.2006.1673260
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Recursive estimation Intelligent networks Monitoring Network topology Object detection Resource management Vehicle dynamics Stochastic processes Optimization methods Sensor systems boundary estimation Sensor deployment EM algorithm maximal likelihood
Content Type	Text
Resource Type	Article

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