The recent dramatic improvements in the performance of commodity hardware has made clusters of workstations or PCs an attractive and economical platform upon which to build scalable database servers. These clusters have large aggregate memory capacities, however, since this global memory is distributed, good algorithms are necessary for memory management, or this large aggregate memory will go underutilized. The goal of the study is to develop and evaluate buffer management algorithms for database clusters. We propose a new buffer management algorithm, remote load sensitive caching (RLS caching), that uses novel techniques to combine data placement with a simple modification of standard client server page replacement algorithms to approximate a global LRU page replacement policy. Through an implementation in the SHORE database system, we evaluate the performance of RLS caching against other buffer management algorithms. Our study demonstrates that RLS caching indeed effectively manages the distributed memory of a server cluster.
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