Performance and scalability of a replica location service

We describe the implementation and evaluate the performance of a replica location service that is part of the Globus Toolkit Version 3.0. A replica location service (RLS) provides a mechanism for registering the existence of replicas and discovering them. Features of our implementation include the use of soft state update protocols to populate a distributed index and optional Bloom filter compression to reduce the size of these updates. Our results demonstrate that RLS performance scales well for individual servers with millions of entries and up to 100 requesting threads. We also show that the distributed RLS index scales well when using Bloom filter compression for wide area updates.