Name
Abstract | ||
|---|---|---|
IoT search engines have attracted increasing attention from both academia and industry, since they are capable of crawling heterogeneous data sources in highly dynamic environment. To process tens of thousands of spatial-temporal-keyword queries per second, query efficiency and communication cost in IoT search engines become critical issues. To address these challenges, caching mechanisms in collaborative edge-cloud computing architecture, which can implement the caching paradigm in cloud for frequent n-hop neighboring activity regions, is proposed in this paper. Thereafter, frequent query results can be achieved quickly leveraging the spatial-temporal-keyword filtering index of n-hop neighbor regions through modeling keywords relevance and uncertain traveling time. Besides, we adopt STK-tree proposed previously to directly answer non-frequent queries. Extensive experiments on real-life dataset demonstrate that our method outperforms the state-of-the-art's techniques in terms of the reduction of the query time and the number of transmitted messages. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICWS49710.2020.00067 | 2020 IEEE International Conference on Web Services (ICWS) |
Keywords | DocType | ISBN |
Spatial-temporal-keyword queries,Collaborative edge-cloud computing,Caching paradigm,Spatial-temporal-keyword filtering index,Frequent query | Conference | 978-1-7281-8787-7 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jine Tang | 1 | 59 | 7.49 |
| Xiao Xue | 2 | 10 | 8.91 |
| Sami Yangui | 3 | 0 | 0.34 |
| Zhangbing Zhou | 4 | 11 | 6.99 |