Name
Abstract | ||
|---|---|---|
Smart sensors are increasingly being used to manage and monitor critical urban infrastructures, e.g., for telecommunication, transport, water, or energy networks, as well as for healthcare or smart buildings. Sensor-based monitoring systems offer ways of continuously monitoring low frequency activities, and open the door to new analytic and predictive applications in Smarter Cities. Such sensors generate “tricklets”, i.e., noisy and continuous time series. Tricklets are typically misaligned, non-uniformly sampled, and comprise low frequency activities and recurring patterns. Storing and making sense of such data in a typical database management system is difficult, due to the impedance mismatch between classical (e.g., relational) data and tricklets. In this paper, we investigate the management of large amounts of tricklets from an architectural perspective, and propose MiSTRAL (MaSsive TRicklets anALysis), an architecture designed for executing low-latency analytics on time series warehouses. MiSTRAL uses a dictionary based representation for tricklets that allows queries to be run natively on compressed representations and thus to achieve the low-latency goal. The architecture of MiSTRAL is presented in detail in the following, along with early experimental results on several Smarter Cities datasets. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/BigData.2013.6691772 | Silicon Valley, CA |
Keywords | Field | DocType |
data analysis,data warehouses,intelligent sensors,time series,town and country planning,MiSTRAL architecture,compressed representations,continuous time series,database management system,dictionary based representation,low frequency activities,low-latency analytics,massive time series,massive tricklets analysis architecture,sensor-based monitoring systems,smart sensors,smarter cities,time series warehouses,tricklets,architecture,data stream,database,dictionary compression,matching pursuit,query execution,sparse time series | Data warehouse,Data mining,Architecture,Dictionary coder,Computer science,Intelligent sensor,Data stream,Artificial intelligence,Building automation,Latency (engineering),Analytics,Machine learning | Conference |
ISSN | Citations | PageRank |
2639-1589 | 5 | 0.46 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marascu, A. | 1 | 5 | 0.46 |
| Pompey, P. | 2 | 9 | 0.93 |
| Eric Bouillet | 3 | 47 | 5.06 |
| Verscheure, O. | 4 | 5 | 0.46 |