By Man, and Cybernetics (1998 : San Diego, Calif.) IEEE International Conference on Systems
The topic of this quantity, "Intelligent platforms for people in Cyberworld", has been chosen to stress the growing to be significance of computational equipment and modelling instruments within the layout, research and keep watch over of clever and data structures.
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Additional info for 1998 IEEE International Conference on Systems, Man, and Cybernetics (1998: San Diego, Calif.)
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.