474 research outputs found

    Information, Energy and Density for Ad Hoc Sensor Networks over Correlated Random Fields: Large Deviations Analysis

    Full text link
    Using large deviations results that characterize the amount of information per node on a two-dimensional (2-D) lattice, asymptotic behavior of a sensor network deployed over a correlated random field for statistical inference is investigated. Under a 2-D hidden Gauss-Markov random field model with symmetric first order conditional autoregression, the behavior of the total information [nats] and energy efficiency [nats/J] defined as the ratio of total gathered information to the required energy is obtained as the coverage area, node density and energy vary.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

    Energy Scaling Laws for Distributed Inference in Random Fusion Networks

    Get PDF
    The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors distributed i.i.d. according to a general spatial distribution in an expanding region. Among the class of data fusion schemes that enable optimal inference at the fusion center for Markov random field (MRF) hypotheses, the scheme with minimum average energy consumption is bounded below by average energy of fusion along the minimum spanning tree, and above by a suboptimal scheme, referred to as Data Fusion for Markov Random Fields (DFMRF). Scaling laws are derived for the optimal and suboptimal fusion policies. It is shown that the average asymptotic energy of the DFMRF scheme is finite for a class of MRF models.Comment: IEEE JSAC on Stochastic Geometry and Random Graphs for Wireless Network

    Energy Efficient Routing for Statistical Inference of Markov Random Fields

    Full text link

    Multiscale representations of Markov random fields

    Get PDF
    Includes bibliographical references (p. 54-58).Supported by the Draper Laboratory IR&D Program. DL-H-418524 Supported by the Office of Naval Research. N00014-91-J-1004 Supported by the Army Research Office of Research. DAAL03-92-G-0115 Supported by the Air Force Office of Scientific Research. F49620-91-C-0047 AFOSR-92-J-0002by Mark R. Luettgen ... [et al.]
    • …
    corecore