Graphical Model Theory for Wireless Sensor Networks

[摘要] Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm.

[发布日期] 2002-12-08 [发布机构] Lawrence Berkeley National Laboratory

[关键词] Probability;Compression;99 General And Miscellaneous//Mathematics, Computing, And Information Science;Graphical Model Theory Sensor Fusion Junction Tree Algorithm Detection Estimation And Classification Distributed Sensing And Control;Classification