Name
Abstract | ||
|---|---|---|
Effective clustering algorithms are indispensable in order to solve the scalability problem in vehicular ad hoc networks. Although current existing clustering algorithms show increased cluster stability under some certain traffic scenarios, it is still hard to address which clustering metric performs the best. In this paper, we propose a unified framework of clustering approach (UFC), composed of ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TITS.2017.2727226 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Clustering algorithms,Measurement,Ad hoc networks,Stability criteria,Prediction algorithms,Heuristic algorithms | Data mining,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Computer science,Sampling (statistics),Wireless ad hoc network,Cluster analysis,Backup,Scalability | Journal |
Volume | Issue | ISSN |
19 | 5 | 1524-9050 |
Citations | PageRank | References |
7 | 0.49 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengying Ren | 1 | 27 | 2.62 |
| Jun Zhang | 2 | 3772 | 190.36 |
| Lyes Khoukhi | 3 | 304 | 44.30 |
| Houda Labiod | 4 | 329 | 42.87 |
| Veronique Veque | 5 | 101 | 17.18 |