@ARTICLE{Wu_04,
    AUTHOR      = {Qishi Wu and Nageswara S. V. Rao and Jacob Barhen and
                   S. Sitharama Iyengar and Vijay K. Vaishnavi and Hairong Qi and Krishnendu Chakrabarty},
    TITLE       = {{On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks}},
    JOURNAL     = {{IEEE Transactions on Knowledge and Data Engineering}},
    YEAR        = {2004},
    VOLUME      = {16},
    NUMBER      = {},
    PAGES       = {740--753},
    MONTH       = {June},
    NOTE        = {},
    KEYWORDS    = {},
    ISBN        = {},
    URL         = {http://csdl.computer.org/comp/trans/tk/2004/06/k0740abs.htm},
    ABSTRACT    = {
                   The problem of computing a route for a mobile agent that incrementally fuses the
                   data as it visits the nodes in a distributed sensor network is considered. The order
                   of nodes visited along the route has a significant impact on the quality and cost
                   of fused data, which, in turn, impacts the main objective of the sensor network,
                   such as target classification or tracking. We present a simplified analytical model
                   for a distributed sensor network and formulate the route computation problem in
                   terms of maximizing an objective function, which is directly proportional to the
                   received signal strength and inversely proportional to the path loss and energy
                   consumption. We show this problem to be NP-complete and propose a genetic algorithm
                   to compute an approximate solution by suitably employing a two-level encoding
                   scheme and genetic operators tailored to the objective function. We present
                   simulation results for networks with different node sizes and sensor distributions,
                   which demonstrate the superior performance of our algorithm over two existing
                   heuristics, namely, local closest first and global closest first methods.
        },
}