Clustering intelligent transportation sensors using public transportation
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Tejswaroop Geetla [1] ; Rajan Batta [1] ; Alan Blatt [2] ; Marie Flanigan [2] ; Kevin Majka [2]
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[1] University at Buffalo (SUNY), USA
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[2] Center for Transportation Injury Research, USA
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- Localización: Top, ISSN-e 1863-8279, ISSN 1134-5764, Vol. 24, Nº. 3, 2016, págs. 594-611
- Idioma: inglés
- DOI: 10.1007/s11750-016-0410-7
- Enlaces
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Resumen
Advanced transportation sensors use a wireless medium to communicate and use data fusion techniques to provide complete information. Large-scale use of intelligent transportation sensors can lead to data bottlenecks in an ad-hoc wireless sensor network, which needs to be reliable and should provide a framework to sensors that constantly join and leave the network. A possible solution is to use public transportation vehicles as data fusion nodes or cluster heads. This paper presents a mathematical programming approach to use public transportation vehicles as cluster heads. The mathematical programming solution seeks to maximize benefit achieved by covering both mobile and stationary sensors, while considering cost/penalty associated with changing cluster head locations. A simulation is developed to capture realistic considerations of a transportation network. This simulation is used to validate the solution provided by the mathematical model.
