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OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data

OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data

Abdulbaki Uzun, Eric Neidhardt, Axel Küpper
Copyright: © 2013 |Volume: 9 |Issue: 4 |Pages: 19
ISSN: 1548-0631|EISSN: 1548-064X|EISBN13: 9781466634961|DOI: 10.4018/ijbdcn.2013100103
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MLA

Uzun, Abdulbaki, et al. "OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data." IJBDCN vol.9, no.4 2013: pp.46-64. http://doi.org/10.4018/ijbdcn.2013100103

APA

Uzun, A., Neidhardt, E., & Küpper, A. (2013). OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data. International Journal of Business Data Communications and Networking (IJBDCN), 9(4), 46-64. http://doi.org/10.4018/ijbdcn.2013100103

Chicago

Uzun, Abdulbaki, Eric Neidhardt, and Axel Küpper. "OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data," International Journal of Business Data Communications and Networking (IJBDCN) 9, no.4: 46-64. http://doi.org/10.4018/ijbdcn.2013100103

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Abstract

Mobile network operators maintain data about their mobile network topology, which is mainly used for network provisioning and planning purposes restricting its full business potential. Utilizing this data in combination with the extensive pool of semantically modeled data in the Linking Open Data Cloud, innovative applications can be realized that would establish network operators as service providers and enablers in the highly competitive services market. In this article, the authors introduce the OpenMobileNetwork (available at http://www.openmobilenetwork.org/) as an open solution for providing approximated network topology data based on the principles of Linked Data along with a business concept for network operators to exploit their valuable asset. Since the quality of the estimated network topology is crucial when providing services on top of it, the authors further analyze and evaluate state-of-the-art approaches for estimating base station positions out of crowdsourced data and discuss the results in comparison to real base station locations.

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