http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
UPBI : An Efficient Index for Continues Probabilistic Range Query of Moving Objects on Road Network
Yaqing Shi,Jun Feng,Zhixian Tang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.5
With the development of mobile terminal technology, the continuous range query of moving objects on road network has been widely applied in the field of transportation, military and communication. In practical applications, the sampling frequency of positioning equipment could not eliminate uncertainty, resulting in moving objects’ position uncertainty between two adjacent samples. The index existing for continues probabilistic range query are based on the centralized or the traditional cluster distributed environment. In this paper, we construct UPBI index structure for the continuous probability range queries on road network based on Hadoop firstly. Secondly, we design the continuous probability range query parallel algorithm considering moving objects’ position uncertainty on road network. Finally, we simultaneously give space constraint R-restrict and the probability calculation method. The experiment demonstrates that index and query algorithm proposed effectively solve the mass data problem about moving objects, and enhance query efficiency.
Hadoop-based Probabilistic Range Queries of Moving Objects on Road Network
Yaqing Shi,Jun Feng,Zhengping Ren,Wenjuan Xie 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.9
With the continuous development of wireless communication and mobile positioning technologies, spatio-temporal queries of moving objects attract more and more attention. In practical application, affected by the sampling frequency of the devices, the position information of moving objects restricted to the road network is often with uncertainty. In this paper, on the basis of the distributed computing framework-Hadoop, it firstly constructs the UPBI index mixing certain and uncertain data. Secondly, it proposes the probabilistic range parallel queries algorithm and the probabilistic calculating method of moving objects on road network. Finally, it gives space constraint r-Restrict to reduce the query scope of the possible path, and simultaneously gives sample pair division to resolve the problem of repetitive calculation. The experiment proves that index and query algorithm proposed effectively solve the mass data problem about moving objects, and enhance query efficiency and precision.