Name
Abstract | ||
|---|---|---|
As traditional network measurement systems store data in relational databases, the storage capacity and computing resource are limited, besides, the extendibility and elasticity are low. The centralized storage scheme will not meet the needs of big data analysis as the data is growing rapidly and continuously. In this paper, we adopt Hadoop and HBase-open source Cloud Computing Frameworks to store network measurement data of non-realtime and realtime applications. The distributed storage scheme is designed to meet the performance demands of storage capacity and computing resource for the mass data. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CCIS.2012.6664268 | Proceedings - 2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems, IEEE CCIS 2012 |
Keywords | DocType | Volume |
distributed data storage,relational databases,network measurement,parallel processing,storage capacity,computing resource,network measurement systems,distributed storage scheme,storage management,cloud computing,hbase,network measurement data storage,hbase-open source cloud computing framework,hadoop,hadoop framework,performance demands | Conference | 2 |
Issue | ISSN | ISBN |
null | null | 978-1-4673-1855-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haijie Ding | 1 | 0 | 0.34 |
| Yuehui Jin | 2 | 5 | 1.51 |
| Cui Yidong | 3 | 9 | 6.35 |
| Tan Yang | 4 | 23 | 10.97 |