Reliable communication in the presence of failures
ACM Transactions on Computer Systems (TOCS)
Preserving and using context information in interprocess communication
ACM Transactions on Computer Systems (TOCS)
Logical Time in Distributed Computing Systems
Computer - Distributed computing systems: separate resources acting as one
The causal ordering abstraction and a simple way to implement it
Information Processing Letters
Lightweight causal and atomic group multicast
ACM Transactions on Computer Systems (TOCS)
Causal controversy at Le Mont St.-Michel
ACM SIGOPS Operating Systems Review
A response to Cheriton and Skeen's criticism of causal and totally ordered communication
ACM SIGOPS Operating Systems Review
Understanding the limitations of causally and totally ordered communication
SOSP '93 Proceedings of the fourteenth ACM symposium on Operating systems principles
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
A New Algorithm to Implement Causal Ordering
Proceedings of the 3rd International Workshop on Distributed Algorithms
A Deterministic Model of Time for Distributed Systems
SPDP '96 Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing (SPDP '96)
Addressing False Causality while Detecting Predicates in Distributed Programs
ICDCS '98 Proceedings of the The 18th International Conference on Distributed Computing Systems
| Hi-index | 0.00 |
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 to model true causal relationships among events. The inefficiency of causal message ordering algorithms takes the form of additional delays in message delivery and requirements for large message buffers. This paper gives a lightweight causal message ordering algorithm based on a modified "happens before" relation. This lightweight algorithm greatly reduces the inefficiencies that traditional causal message ordering algorithms suffer from, by reducing the problem of false causality.