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
Link To Document :
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