.png){kind=icon}
Return
Dynamic trajectory partition optimization method based on historical trajectory data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2023.111120.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Partitioning dynamic trajectory data can improve the efficiency and accuracy of trajectory data processing, provide a foundation for trajectory data mining and analysis. However, with the continuous growth of trajectory data scales and the urgent demand for trajectory query efficiency and accuracy, partitioning methods have become crucial. The partitioning method of dynamic trajectory data faces significant challenges in terms of spatiotemporal trajectory locality, partition load balancing, and partition time. To address these challenges, we propose a method based on historical trajectory pre-partitioning, which can store data more effectively in distributed systems. We partition similar historical trajectory data to achieve preliminary partitioning of the data. In addition, we also construct a cost model to ensure that the workload of each partition is close to consistency. Extensive experiments have demonstrated the excellent partitioning efficiency and query efficiency achieved by our design compared to other partitioning methods.
Keywords:
Pre-partitioning
Dynamic trajectory partitioning
Similarity function
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W
Organization
View more organizations
Cited Papers
ShareSaveIncorporation of Metalloporphyrin Inhibitors of Heme Oxygenase into Micelles and Liposomes.png)
Pharmacology
PharmacologyIF0
PREAI
ShareSave
Gender and Job Satisfaction in Urban China: The Role of Individual, Family, and Job Characteristics
PREAI
ShareSave
ShareSave View more