We propose a scalable distributed data structure (SDDS) called SD-Rtree. We intend our structure for point, window and k NN queries over large spatial datasets distributed on clusters of interconnected servers. The structure balances the storage and processing load over the available resources, and aims at minimizing the size of the cluster. SD-Rtree generalizes the well-known Rtree structure. It uses a distributed balanced binary tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. A user/application manipulates the structure from a client node. The client addresses the tree through its image that can be possibly outdated due to later split. This may generate addressing errors, solved by the forwarding among the servers. Specific messages towards the clients incrementally correct the outdated images. We present the building of an SD-Rtree through insertions, focusing on the split and rotation algorithms. We follow with the query algorithms. We describe then a flexible allocation protocol which allows to cope with a temporary shortage of storage resources through data storage balancing. Experiments show additional aspects of SD-Rtree and compare its behavior with a distributed quadtree. The results justify our various design choices and the overall utility of the structure.
The VLDB Journal – Springer Journals
Published: Aug 1, 2009
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera