- ABND+87.H. Attiya, A. Bar-Noy, D. Dolev, D. Koller, D. Peleg, and R. Reischuk. Achievable Cases in an Asynchronous Environment. In IEEE Symposium on Foundations of Computer Science. IEEE, 1987.Google ScholarDigital Library
- ADG84.H. Attiya, D. Dolev, and J. Gil. Asynchronous Byzantine Consensus. In A CM Symposium on Principles of Distributed Computing. ACM, 1984. Google ScholarDigital Library
- BMZ88.O. Biran, S. Moran, and S. Zaks. A Combinatorial Characterization of the Distributed Tasks Solvable in the Presence of One Faulty Processor. In A CM Symposium on Principles of Distributed Computing. ACM, 1988. Google ScholarDigital Library
- BO83.M. Ben-Or. Another Advantage of Free Choice : Completely Asynchronous Agreement Protocols. In A CM Symposium on Principles of Distributed Computing. ACM, 1983. Google ScholarDigital Library
- Bra85.G. Bracha. An O(log n) Expected Rounds Randomized Byzantine Generals Algorithm. In A CM Symposium on Theory of Computing, 1985. Google ScholarDigital Library
- BW87.M.F. Bridgland and R. J. Watro. Fault Tolerant Decision Making in Totally Asynchronous Systems. In A CM Symposium on Principles of Distributed Computing. ACM, 1987. Google ScholarDigital Library
- DDS83.D. Dolev, C. Dwork, and L. Stockmeyer. On the Minimal Synchronism Needed for Distributed Consensus. In IEEE Symposium on Foundations of Computer Science. IEEE, 1983. A revised version appeared in JACM 34 (January 1987). Google ScholarDigital Library
- DLS84.C. Dwork, N. Lynch, and L. Stockmeyer. Consensus in the Presence of Partial Synchrony. In A CM Symposium on Principles of Distributed Computing. ACM, 1984.Google Scholar
- FLP83.M. Fischer, N. Lynch, and M. Paterson. Impossiblity of Distributed Consensus with One Faulty Protess. In A CM Symposium on Principles of Database Systems, 1983. A revised version appeared in JACM 32 (April 1985). Google ScholarDigital Library
- Rab83.M. Rabin. Randomized Byzantine Generals. In IEEE Symposium on Foundations of Computer Science. IEEE, 1983.Google Scholar
Index Terms
- Agreement is harder than consensus: set consensus problems in totally asynchronous systems
Recommendations
Asynchronous consensus and broadcast protocols
A consensus protocol enables a system of n asynchronous processes, some of which are faulty, to reach agreement. There are two kinds of faulty processes: fail-stop processes that can only die and malicious processes that can also send false messages. ...
Uniform consensus is harder than consensus
We compare the consensus and uniform consensus problems in synchronous systems. In contrast to consensus, uniform consensus is not solvable with byzantine failures. This still holds for the omission failure model if a majority of processes may be ...
Parallel Consensus is Harder than Set Agreement in Message Passing
ICDCS '13: Proceedings of the 2013 IEEE 33rd International Conference on Distributed Computing SystemsIn the traditional consensus task, processes are required to agree on a common value chosen among the initial values of the participating processes. It is well known that consensus cannot be solved in crash-prone, asynchronous distributed systems. Two ...
Comments