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 …

The causal order in distributed asynchronous systems is a valuable and useful concept to
implement distributed algorithms. In particular, causal broadcasts have been used to solve …

This paper presents a new algorithm to implement causal ordering. Causal ordering was first
proposed in the ISIS system developed at Cornell University. The interest of causal ordering …

A significant shortcoming of causal message ordering systems is their inefficiency because
of false causality. False causality is the result of the inability of the “happens before” relation …

Causal message ordering is a partial ordering of messages in a distributed computing
environment. It places a restriction on communication between processes by requiring that if …

Causality in distributed systems is a concept that has long been explored and numerous
approaches have been made to use causality as a way to trace distributed system …

Asynchronous execution of processes and unpredictable communication delays create
nondeterminism in distributed systems that complicates the design, verification, and analysis …

Several scalable constant size clocks were proposed in the literature for tracking causality of
events in distributed systems with a high accuracy, even though they do capture but not …

Dependency knowledge of the form “x is independent of y once z is known” invariably obeys
the four graphoid axioms, examples include probabilistic and database dependencies …

An optimal causal message ordering algorithm was recently proposed by Kshemkalyani and
Singhal, and its optimality was proved theoretically. For a system of n processes, although …