The design and analysis of spatial data structures
The design and analysis of spatial data structures
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Communications of the ACM
A class of data structures for associative searching
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
Quality of service in an information economy
ACM Transactions on Internet Technology (TOIT)
Supporting Multi-Dimensional Range Queries in Peer-to-Peer Systems
P2P '05 Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing
Grid-Based Data Stream Processing in e-Science
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
Using a distributed quadtree index in peer-to-peer networks
The VLDB Journal — The International Journal on Very Large Data Bases
Querying the internet with PIER
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Proceedings of the VLDB Endowment
Scalable community-driven data sharing in e-science grids
Future Generation Computer Systems
Workload-aware data partitioning in community-driven data grids
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Collaborative query coordination in community-driven data grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
A distributed recommender system architecture
International Journal of Web Engineering and Technology
| Hi-index | 0.00 |
Many e-science communities, e. g., medicine, climatology, and astrophysics, are overwhelmed by the exponentially growing data volumes that need to be accessible by collaborating researchers. Nowadays, new scientific results are often obtained by exploring and cross-correlating data from different distributed sources [3]. However, neither centralized data processing by shipping the data to the processing site on demand nor a centralized data warehouse approach scale sufficiently to handle the huge data volumes and processing demands of future e-science communities and applications. The former suffers from high transmission costs while the latter cannot scale to the large amounts of data in combination with the growing number of queries.