| Title |
A Novel Real-Time Edge-Cloud Big Data Management and Analytics Framework for Smart Cities |
| ID_Doc |
44720 |
| Authors |
Cavicchioli, R; Martoglia, R; Verucchi, M |
| Title |
A Novel Real-Time Edge-Cloud Big Data Management and Analytics Framework for Smart Cities |
| Year |
2022 |
| Published |
Journal Of Universal Computer Science, 28, 1 |
| DOI |
10.3897/jucs.71645 |
| Abstract |
Exposing city information to dynamic, distributed, powerful, scalable, and user-friendly big data systems is expected to enable the implementation of a wide range of new opportunities; however, the size, heterogeneity and geographical dispersion of data often makes it difficult to combine, analyze and consume them in a single system. In the context of the H2020 CLASS project, we describe an innovative framework aiming to facilitate the design of advanced big-data analytics workflows. The proposal covers the whole compute continuum, from edge to cloud, and relies on a well-organized distributed infrastructure exploiting: a) edge solutions with advanced computer vision technologies enabling the real-time generation of "rich" data from a vast array of sensor types; b) cloud data management techniques offering efficient storage, real-time querying and updating of the high-frequency incoming data at different granularity levels. We specifically focus on obstacle detection and tracking for edge processing, and consider a traffic density monitoring application, with hierarchical data aggregation features for cloud processing; the discussed techniques will constitute the groundwork enabling many further services. The tests are performed on the real use-case of the Modena Automotive Smart Area (MASA). |
| Author Keywords |
smart city framework; big data management; edge computing; cloud data management |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000750009100001 |
| WoS Category |
Computer Science, Software Engineering; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://lib.jucs.org/article/71645/download/pdf/
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