Optimal file distribution for partial match retrieval
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Access methods for multiversion data
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Optimal disk allocation for partial match queries
ACM Transactions on Database Systems (TODS)
Disk allocation for Cartesian product files on multiple-disk systems
ACM Transactions on Database Systems (TODS)
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
PDIS '93 Proceedings of the second international conference on Parallel and distributed information systems
Efficient Management of Time-Evolving Databases
IEEE Transactions on Knowledge and Data Engineering
An Efficient Multiversion Access Structure
IEEE Transactions on Knowledge and Data Engineering
LoT: Dynamic Declustering of TSB-Tree Nodes for Parallel Access to Temporal Data
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Declustering Techniques for Parallelizing Temporal Access Structures
Proceedings of the Tenth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
An asymptotically optimal multiversion B-tree
The VLDB Journal — The International Journal on Very Large Data Bases
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
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In this paper we address the problem of declustering temporal data and access structures for parallel architectures consisting of a single processor and multiple disks. To illustrate our techniques we choose the recently proposed Multi-Version Access Structure. We propose two new, efficient techniques called T-proximity and KT-proximity for assigning the data and index nodes of the multiversion access structure to multiple disks. The KT-proximity declustering technique considers both the key and temporal dimensions of the data in the nodes to achieve uniform load distribution and decrease the response time for key-range, time-range and combined range queries. The T-proximity technique considers only the temporal dimension.Extensive simulations of the T-proximity and KT-proximity techniques validate their efficiency. Our results demonstrate that this technique outperforms previous methods based on random, multi-level round-robin, the LoT scheme, and proximity based on time only. Finally, we emphasize that KT-proximity is a general technique applicable to any temporal access structure.