Adlib: A Self-Tuning Index for Dynamic Peer-to-Peer Systems

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.