Abstract
The paper proposes a new approach to model the Brown Planthopper surveillance as a synchronous network, network consists of components running simultaneously, based on hexagonal cellular automata. In the surveillance network, working space of hoppers is divided as a hexagonal cell system of which cell is a node of a graph G and two neighborhood cells compose an edge of the graph. Sensor nodes are deployed at some cells to measure surrounding conditions as well as hopper density. Simulation results of the hopper surveillance network model with data collection in Cantho, Mekong Delta may provide some useful information in managing pest insects as well as in sensing and collecting data from observation wireless sensor network.
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Acknowledgments
The work of this paper was in the scope of the “OBSNET - Optimizing the Brown Planthopper surveillance network using automatic light traps in the Mekong Delta region” project of the Ministry of Education and Training, Vietnam. The first author was funded by the program 911 of Ministry of Education and Training, Vietnam.
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Lam, B.H., Huynh, HH., Huynh, H.X., Pottier, B. (2016). A Synchronous Network for Brown Planthopper Surveillance Based on Hexagonal Cellular Automata. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_10
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DOI: https://doi.org/10.1007/978-3-319-46909-6_10
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