Home // International Journal On Advances in Intelligent Systems, volume 7, numbers 3 and 4, 2014 // View article

Provide a Real-World Graph Suitable for the Mathematical Optimization of Communication Networks

Authors:
Markus Prossegger

Keywords: geographic information; spatial data; communication network optimization; normalized geobasisdata.

Abstract:
One of the main reasons of the hesitant expansion of fiber optic communication networks is the large financial expense for the excavation work. While the cost for (passive) hardware components and the fiber optics cable itself have fallen during the last decade, the cable layout work is still the cost driver of network construction projects. The most promising approach for a valid cost estimation is to use state-of-the-art network simulation and optimization techniques in the field of operations research. This study examines an automated process of generating a network graph that closes the missing link between the real-world and mathematical optimization of a communication network. The constructed graph is based on heterogeneous spatial data and weighted with real-world construction costs. It is then used to solve the minimum Steiner tree problem as typical optimization problem for the modeling and optimization of communication networks. While the applied mathematical model is studied in detail, the quality of the result as well as the runtime performance of the optimization algorithm is heavily dependent on the complexity and validity of the input graph. Based on a general format, the normalized geobasisdata, an initial graph, is constructed. This graph is then used as input into our rule-based system to select and weight the edges to be in the final graph. The optimization results of the experiments on realworld data, prove the effectiveness and efficiency of the proposed approach.

Pages: 751 to 761

Copyright: Copyright (c) to authors, 2014. Used with permission.

Publication date: December 30, 2014

Published in: journal

ISSN: 1942-2679