TY - GEN
T1 - Perormance of TPR*-trees for predicting future positions of moving objects in U-cities
AU - Jang, Min Hee
AU - Kim, Sang Wook
AU - Shin, Miyoung
PY - 2007
Y1 - 2007
N2 - The TPR*-tree is the most widely-used index structure for effectively predicting the future positions of moving objects. The TPR*-tree, however, has the problem that both of the dead space in a bounding region and the overlap among bounding regions become larger as the prediction time point in the future gets farther. This makes more nodes within the TPR*-tree accessed in query processing time, which incurs serious performance degradation. In this paper, we examine the performance problem quantitatively via a series of experiments. First, we show how much the performance deteriorates as a prediction time point gets farther from the present, and also show how the frequent updates of positions of moving objects alleviate this problem. Our contribution would help provide important clues to devise strategies improving the performance of TPR*-trees further.
AB - The TPR*-tree is the most widely-used index structure for effectively predicting the future positions of moving objects. The TPR*-tree, however, has the problem that both of the dead space in a bounding region and the overlap among bounding regions become larger as the prediction time point in the future gets farther. This makes more nodes within the TPR*-tree accessed in query processing time, which incurs serious performance degradation. In this paper, we examine the performance problem quantitatively via a series of experiments. First, we show how much the performance deteriorates as a prediction time point gets farther from the present, and also show how the frequent updates of positions of moving objects alleviate this problem. Our contribution would help provide important clues to devise strategies improving the performance of TPR*-trees further.
UR - https://www.scopus.com/pages/publications/39649116664
U2 - 10.1007/978-3-540-72830-6_88
DO - 10.1007/978-3-540-72830-6_88
M3 - Conference contribution
AN - SCOPUS:39649116664
SN - 9783540728290
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 841
EP - 850
BT - Agent and Multi-Agent Systems
PB - Springer Verlag
T2 - 1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007
Y2 - 31 May 2007 through 1 June 2007
ER -