Adlib: a self-tuning index for dynamic peer-to-peer systems

international conference on data engineering(2005)

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摘要
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.
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关键词
adlib self-tuning index,dynamic peer-to-peer systems,realistic workloads,overall system cost,dynamic set,query efficiency,database indexing,optimal configuration change,dynamically adapts,optimal trade-off point,self-tuning index,very large databases,peer-to-peer computing,index maintenance cost,large database,query processing,data engineering,distributed systems,indexing,sun,databases,cost function,indexation
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