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

Comprehensive distributed garbage collection an object-oriented 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 ap-proaches: 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 comprehen-save distributed garbage collection that entails comput-ing the vector-time characterising the causal history of some relevant events of the mutator processes compu-tations. 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 iden-tify garbage is possible without the unbounded space overheads usually associated with dynamically recon-structing vector-times of arbitrary events of distributed computations. Our approach integrates a lazy log-keeping mechanism and therefore tackles both of the aforementioned stumbling blocks of distributed garbage collection