| Title |
A Data Cube Model for Analysis of High Volumes of Ambient Data |
| ID_Doc |
43317 |
| Authors |
Gui, H; Roantree, M |
| Title |
A Data Cube Model for Analysis of High Volumes of Ambient Data |
| Year |
2012 |
| Published |
|
| DOI |
10.1016/j.procs.2012.06.016 |
| Abstract |
Ambient systems generate large volumes of data for many of their application areas with XML often the format for data exchange. As a result, large scale ambient systems such as smart cities require some form of optimization before different components can merge their data streams. In data warehousing, the cube structure is often used for optimizing the analytics process with more recent structures such as dwarf, providing new orders of magnitude in terms of optimizing data extraction. However, these systems were developed for relational data and as a result, we now present the development of an XML dwarf to manage ambient systems generating XML data. (C) 2011 Published by Elsevier Ltd. |
| Author Keywords |
Ambient Data Analysis; Sensors; Smart City; OLAP |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000314400700012 |
| WoS Category |
Computer Science, Hardware & Architecture; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://doi.org/10.1016/j.procs.2012.06.016
|