By Nan Chen, Lidan Shou, Gang Chen, Ke Chen, Yunjun Gao (auth.), Hiroyuki Kitagawa, Yoshiharu Ishikawa, Qing Li, Chiemi Watanabe (eds.)
This quantity set LNCS 5981 and LNCS 5982 constitutes the refereed court cases of the fifteenth foreign convention on Database structures for complex purposes, DASFAA 2010, held in Tsukuba, Japan, in April 2010. The 39 revised complete papers and sixteen revised brief papers provided including three invited keynote papers, 22 demonstration papers, 6 commercial papers, and a pair of keynote talks have been rigorously reviewed and chosen from 285 submissions. The papers of the 1st quantity are geared up in topical sections on P2P-based applied sciences, info mining applied sciences, XML seek and matching, graphs, spatial databases, XML applied sciences, time sequence and streams, complex facts mining, question processing, internet, sensor networks and communications, details administration, in addition to groups and net graphs. the second one quantity comprises contributions regarding trajectories and relocating items, skyline queries, privateness and safeguard, facts streams, similarity seek and occasion processing, garage and complex themes, commercial, demo papers, and tutorials and panels.
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Extra info for Database Systems for Advanced Applications: 15th International Conference, DASFAA 2010, Tsukuba, Japan, April 1-4, 2010, Proceedings, Part II
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In this way, the B s -tree keeps good and smooth overall performance despite the change of the workload. It can be seen that in almost all cases, the B s -tree outperforms the TPR*-tree and the Bx -tree in overall performance. ϯϬ Ϯϱ ϮϬ džͲƚƌĞĞ ƐͲƚƌĞĞ dWZΎͲƚƌĞĞ ϭϱ ϭϬ ϱ Ϭ ϭ͗ϭϬϬϬ ϭ͗ϭϬϬ ϭ͗ϭϬ ϭ͗ϭ ϭϬ͗ϭ ϭϬϬ͗ϭ ηŽĨYƵĞƌŝĞƐ͗ηŽĨhƉĚĂƚĞƐ ;ďͿKǀĞƌĂůůWhdŝŵĞ Fig. 6. 3 Self-tuning Performance The above experiments show that the Bs -tree has good performance when it reaches the steady states. However, if the performance degrades markedly when the B s -tree is in the 14 N.
2 Self-tuning Framework From the above analysis, we find that the update and query performance of the B s -tree can be tuned by the update parameter α and the query parameter β. However, α and β can not be changed arbitrarily. We should guarantee the correctness of the queries. Theorem 1. As long as β is no less than all α of all moving objects, the query correctness of the Bs -tree can be guaranteed. That is, given a query, the B s -tree can find all moving objects which satisfy the query in their t per s.
T otal T RJ = k else remove C from group of clusters Translate representative trajectories into output format Fig. 3. An Outline of Clustering-based Anonymization Algorithm Definition 4. (Strict k-anonymity over trajectories): Let T rj be a trajectory. We say T rj satisfies strict k-anonymity if Support(Trj) is no less than k. 2 Finding Candidate Clusters In this subsection, we present how to find a candidate cluster for a new trajectory during the clustering-based anonymization. The first step is to check whether a new trajectory can be absorbed by an existing cluster according to the distance metric.