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EnglishThis paper copes with the issue of extracting mobility patterns in a urban computing scenario. The computation is parallelized by partitioning the territory into a number of regions. In each region a computing node collects data from a set of local sensors, analyzes the data and coordinates with neighbor regions to extract the mobility patterns. We propose and analyze a “local” synchronization approach, where computation regarding a specific region is performed using the information received from a subset of neighbor regions. When opposed to the usual approach, where the computation proceeds after collecting the results from all the regions, our approach offers notable benefits: reduction of computation time, real-time model extraction, better support to local decisions. The paper describes the model of local synchronization by means of a Petri net and analyzes the performance in terms of the ability of the system of keeping the pace with the data collected by sensors. The analysis is based on a real world dataset tracing the movements of taxis in the urban area of Beijing.
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| Titolo: | Distributed computation of mobility patterns in a smart city environment | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Serie: | ||
| Handle: | http://hdl.handle.net/20.500.11770/303515 | |
| ISBN: | 978-3-030-10548-8 978-3-030-10549-5 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/20.500.11770/303515
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