Incremental garbage collection for causal relationship computation in distributed systems
R. Medina · 2002
Many distributed applications require the knowledge of the causality relation induced by the computation. Reconstructing this relation appears to be an interesting tool for such applications, but a vector of size S - where S is the number of processes - must be attached to each event to achieve this reconstruction. This induces a large overhead in secondary memory. After defining special events of the computation - some kind of checkpoints - we propose two algorithms that discard unnecessary data for the causal relationship reconstruction. The first algorithm acts on-the-fly while the second acts during reconstruction.>