Abstract
Many applications associated with the smart city experience rely on spatio-temporal data. Specific use-cases include location-dependent real-time traffic, weather and pollution reports. Data is traditionally sampled using stationary sensors, however, in densely populated areas one could envisage crowd-sensing data collection schemes where cars, bikes and pedestrians collect information in transit and transmit it to a service provider through one of either a fast mobile network such as LTE(4G) or by Wifi/Gossip communication. While mobile sensors reduce the need for expensive infrastructure, the downside is that performance characteristics of data coverage and transmission are less reliable and harder to predict. In this paper we present a generic model to investigate the robustness and efficiency of LTE/Gossip hybrid data transmission strategies for crowd-sensing networks that are not amenable to mean-field analysis. To illustrate our model’s scalability, we fit it to journey data from the London Cycle Hire scheme.
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Guenther, M.C., Bradley, J.T. (2014). On Performance of Gossip Communication in a Crowd-Sensing Scenario. In: Norman, G., Sanders, W. (eds) Quantitative Evaluation of Systems. QEST 2014. Lecture Notes in Computer Science, vol 8657. Springer, Cham. https://doi.org/10.1007/978-3-319-10696-0_10
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DOI: https://doi.org/10.1007/978-3-319-10696-0_10
Publisher Name: Springer, Cham
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