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A GRASS GIS parallel module for radio-propagation predictions

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Geographical information systems are ideal candidates for the application of parallel programming techniques, mainly because they usually handle large data sets. To help us deal with complex calculations over such data sets, we investigated the performance constraints of a classic master–worker parallel paradigm over a message-passing communication model. To this end, we present a new approach that employs an external database in order to improve the calculation–communication overlap, thus reducing the idle times for the worker processes. The presented approach is implemented as part of a parallel radio-coverage prediction tool for the Geographic Resources Analysis Support System (GRASS) environment. The prediction calculation employs digital elevation models and land-usage data in order to analyze the radio coverage of a geographical area. We provide an extended analysis of the experimental results, which are based on real data from an Long Term Evolution (LTE) network currently deployed in Slovenia. Based on the results of the experiments, which were performed on a computer cluster, the new approach exhibits better scalability than the traditional master–worker approach. We successfully tackled real-world-sized data sets, while greatly reducing the processing time and saturating the hardware utilization.
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Keywords: GIS; GRASS; master–worker paradigm; parallel computing; radio propagation; simulation

Document Type: Research Article

Affiliations: 1: Research and Development Department, Telekom Slovenije, d.d., Cigaletova ulica 15, SI-1000, Ljubljana, Slovenia 2: Nagasaki Advanced Computer Center, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki-city, Nagasaki, 852-8521, Japan 3: Computer Systems Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000, Ljubljana, Slovenia

Publication date: April 3, 2014

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