DocumentCode
2847280
Title
Adlib: a self-tuning index for dynamic peer-to-peer systems
Author
Ganesan, Prasanna ; Sun, Qixiang ; Garcia-Molina, Hector
Author_Institution
Stanford Univ., CA, USA
fYear
2005
fDate
5-8 April 2005
Firstpage
256
Lastpage
259
Abstract
Peer-to-peer (P2P) systems enable queries over a large database horizontally partitioned across a dynamic set of nodes. We devise a self-tuning index for such systems that can trade off index maintenance cost against query efficiency, in order to optimize the overall system cost. The index, Adlib, dynamically adapts itself to operate at the optimal trade-off point, even as the optimal configuration changes with nodes joining and leaving the system. We use experiments on realistic workloads to demonstrate that Adlib can reduce the overall system cost by a factor of four.
Keywords
database indexing; peer-to-peer computing; query processing; very large databases; Adlib self-tuning index; dynamic peer-to-peer systems; index maintenance cost; large database; optimal trade-off point; query efficiency; Cost function; Data engineering; Databases; IEEE news; Indexing; Peer to peer computing; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on
ISSN
1084-4627
Print_ISBN
0-7695-2285-8
Type
conf
DOI
10.1109/ICDE.2005.19
Filename
1410128
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