Name
Abstract | ||
|---|---|---|
Recent years have seen an increasing number of traffic surveillance cameras deployed on the main roads and intersections of metropolitan areas. For large and ediumsized cities, these cameras generate an enormous amount of data. Existing solutions based relational database systems cannot effectively manage and process such large volume of data, nor can they provide support for efficient and scalable support for either analytical tasks or tasks requiring response in real-time. To address these challenges, we have developed the GrandLand Traffic Data Processing Platform (GLPlatform) to provide distributed, scalable processing of traffic surveillance data. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/BigData.Congress.2014.113 | BigData Congress |
Keywords | Field | DocType |
relational databases,big data,traffic data, data processing systems, big data,traffic engineering computing,data processing systems,grandland traffic data processing platform,traffic data,solutions based relational database systems,glplatform,distributed scalable processing,traffic surveillance data | Data mining,Data processing,Computer science,Floating car data,Data processing system,Relational database management system,Metropolitan area,Big data,Database,Scalability | Conference |
ISSN | Citations | PageRank |
2379-7703 | 4 | 0.44 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xingcan Cui | 1 | 4 | 1.12 |
| Zhen Dong | 2 | 4 | 0.44 |
| Liwei Lin | 3 | 122 | 28.76 |
| Renyong Song | 4 | 4 | 0.44 |
| Xiaohui Yu | 5 | 869 | 64.75 |