Name
Abstract | ||
|---|---|---|
Many novel and exhilarating applications emerged in the past decade, thanks to the ubiquity and the volume of data in this big data era. However, large-scale data collection is often expensive and time-consuming, especially in the physical world. To address this issue, in this paper, we study a new research problem, named k-Collector Problem (k -CP), which considers to minimize the data collection time for a set of k data collectors in the road network. We propose a constant-ratio approximation algorithm, called Collective Search Walk Planning (CSP). Moreover, we also discuss different strategies to boost the efficiency of CSP. Experimental results on 3 real datasets show that our proposed CSP algorithm outperforms other baselines in both solution quality and efficiency. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/GLOBECOM38437.2019.9013472 | IEEE Global Communications Conference |
Keywords | DocType | ISSN |
Big data collection,routing in road networks,approximation algorithm | Conference | 2334-0983 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bay-Yuan Hsu | 1 | 10 | 2.68 |
| Chih-Ya Shen | 2 | 103 | 17.13 |
| Guang-Siang Lee | 3 | 0 | 0.34 |
| Yun-Jui Hsu | 4 | 0 | 0.34 |
| Chen-Hsu Yang | 5 | 0 | 0.34 |
| Chen-Wei Lu | 6 | 0 | 0.34 |
| Ming-Yi Chang | 7 | 4 | 1.87 |
| Kei-Peng Lin | 8 | 0 | 0.34 |