Title
Diffusion-based EM algorithm for distributed estimation of Gaussian mixtures in wireless sensor networks.
Abstract
Distributed estimation of Gaussian mixtures has many applications in wireless sensor network (WSN), and its energy-efficient solution is still challenging. This paper presents a novel diffusion-based EM algorithm for this problem. A diffusion strategy is introduced for acquiring the global statistics in EM algorithm in which each sensor node only needs to communicate its local statistics to its neighboring nodes at each iteration. This improves the existing consensus-based distributed EM algorithm which may need much more communication overhead for consensus, especially in large scale networks. The robustness and scalability of the proposed approach can be achieved by distributed processing in the networks. In addition, we show that the proposed approach can be considered as a stochastic approximation method to find the maximum likelihood estimation for Gaussian mixtures. Simulation results show the efficiency of this approach.
Year
DOI
Venue
2011
10.3390/s110606297
SENSORS
Keywords
Field
DocType
diffusion,distributed processing,EM algorithm,consensus,wireless sensor networks
Sensor node,Key distribution in wireless sensor networks,Mathematical optimization,Expectation–maximization algorithm,Computer science,Algorithm,Brooks–Iyengar algorithm,Electronic engineering,Distributed algorithm,Gaussian,Wireless sensor network,Scalability
Journal
Volume
Issue
ISSN
11
6
1424-8220
Citations 
PageRank 
References 
18
0.79
21
Authors
3
Name
Order
Citations
PageRank
qingan112212.38
Wendong Xiao246728.64
Lihua Xie35686405.63