The drinking philosophers problem
ACM Transactions on Programming Languages and Systems (TOPLAS) - Lecture notes in computer science Vol. 174
Information Processing Letters
Termination detection for dynamically distributed systems with non-first-in-first-out communication
Journal of Parallel and Distributed Computing
An optimal algorithm for distributed snapshots with causal message ordering
Information Processing Letters
Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Distributed termination detection for dynamic systems
Parallel Computing
ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed deadlock detection
ACM Transactions on Computer Systems (TOCS)
An optimal algorithm for mutual exclusion in computer networks
Communications of the ACM
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Efficient detection of a class of stable properties
Distributed Computing
Strong stable properties in distributed systems
Distributed Computing
Protocols for Deadlock Detection in Distributed Database Systems
IEEE Transactions on Software Engineering
Detecting stable locality-aware predicates
Journal of Parallel and Distributed Computing
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Monitoring a distributed system to detect a stable property is an important problem with many applications. The problem is especially challenging for a dynamic distributed system because the set of processes in the system may change with time. In this paper, we present an efficient algorithm to determine whether a stable property has become true in a system in which processes can join and depart the system at any time. Our algorithm is based on maintaining a spanning tree of processes that are currently part of the system. The spanning tree, which is dynamically changing, is used to periodically collect local states of processes such that: (1) all local states in the collection are consistent with each other, and (2) the collection is complete, that is, it contains all local states that are necessary to evaluate the property and derive meaningful inferences about the system state. Unlike existing algorithms for stable property detection in a dynamic environment, our algorithm is general in the sense that it can be used to evaluate any stable property. Further, it does not assume the existence of any permanent process. Processes can join and leave the system while the snapshot algorithm is in progress.