Comprehensive Distributed Garbage Collection by Tracking Causal Dependencies of Relevant Mutator Events

Comprehensive distributed garbage collection an objectoriented distributed systems has mostly been addressed via distributed versions of graph-tracing algorithms, a legacy of centralised garbage collection techniques. Two features jeopardise the scalability of these approaches: the bottleneck associated with having t o reach a global consensus before any resource can actually be reclaimed, and the overhead of eager log-keeping. This paper describes an alternative approach to comprehensave distributed garbage collection that entails computing the vector-time characterising the causal history of some relevant events of the mutator processes computations. Knowing the causal histories of these events makes it possible to identify garbage objects that are not identifiable b y means of per-site garbage collection alone. Computing the vector-times necessary to identify garbage is possible without the unbounded space overheads usually associated with dynamically reconstructing vector-times of arbitrary events of distributed computations. Our approach integrates a lazy logkeeping mechanism and therefore tackles both of the aforementioned stumbling blocks of distributed garbage collection,