SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
On-line reorganization of sparsely-populated B+-trees
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Towards self-tuning data placement in parallel database systems
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
A Case for NOW (Networks of Workstations)
IEEE Micro
Spatial queries in sensor networks
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Multiple range query optimization with distributed cache indexing
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
An efficient peer-to-peer indexing tree structure for multidimensional data
Future Generation Computer Systems
Online reorganization of databases
ACM Computing Surveys (CSUR)
Self-tuning management of update-intensive multidimensional data in clusters of workstations
The VLDB Journal — The International Journal on Very Large Data Bases
Multiple query scheduling for distributed semantic caches
Journal of Parallel and Distributed Computing
An approach for heterogeneous and loosely coupled geospatial data distributed computing
Computers & Geosciences
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
P2PR-Tree: an R-tree-based spatial index for peer-to-peer environments
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
vCRIB: virtualized rule management in the cloud
HotCloud'12 Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing
Scalable and dynamically balanced shared-everything OLTP with physiological partitioning
The VLDB Journal — The International Journal on Very Large Data Bases
Scalable rule management for data centers
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
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In order to provide fast and timely answers to queries in the context of spatial databases and GIS, we present our solution for effective data migration and tuning strategies in shared-nothing parallel spatial databases. Our purpose is to improve the performance of the indexes. Our approach has the following features. First, our scheme is self-tuning, dynamic as well as query-centric and it can adapt to dynamically changing user access patterns. Second, a global distributed R-tree-based indexing method is employed to facilitate effective data migration. Third, unlike traditional partitioning strategies where each processing element (PE) contains data from a single region of space, we allow each PE to store data from multiple and disjoint regions. This minimizes overlap in regions as well as coverage.We implemented the proposed scheme and conducted an extensive performance study on Fujitsu's AP3000 machine with 32 workstations using real datasets. Our experimental results show that our load-balancing strategy can distribute the load effectively across the PEs in the system, thereby reducing response times of incoming queries.