Dynamic SEOF: An Adaptable Object Prefetch Policy for Object-oriented Database Systems

When accessing objects in an object-oriented database, performance can be greatly improved by prefetching objects efficiently. In this paper we present a new object prefetch policy, dynamic selective eager object fetch (SEOF), which prefetches objects only from selected candidate pages without using any high-level object semantics. Our policy considers both correlations and frequencies of fetching objects when selecting prefetch candidates. Unlike existing prefetch policies, dynamic SEOF utilizes the memory and the swap space of clients efficiently without resource exhaustion. Furthermore, the proposed policy has good adaptability to both the effectiveness of clustering and database size. It also adjusts the degree of prefetching dynamically according to the working environment. We show the performance of the proposed policy through experiments over various multi-client system configurations.

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