Understanding fault-tolerant distributed systems
Communications of the ACM
Neural network design
Experience in industrial plant model development using large-scale artificial neural networks
Information Sciences: an International Journal - Special issue on advanced neuro-fuzzy techniques and their applications
Byzantine Agreement in the Presence of Mixed Faults on Processors and Links
IEEE Transactions on Parallel and Distributed Systems
Cryptography and network security (2nd ed.): principles and practice
Cryptography and network security (2nd ed.): principles and practice
Reliable computer systems (3rd ed.): design and evaluation
Reliable computer systems (3rd ed.): design and evaluation
Reaching strong consensus in the presence of mixed failure types
Information Sciences—Informatics and Computer Science: An International Journal
Consensus under unreliable transmission
Information Processing Letters
Reaching Agreement in the Presence of Faults
Journal of the ACM (JACM)
The Weak Byzantine Generals Problem
Journal of the ACM (JACM)
The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Information Sciences—Informatics and Computer Science: An International Journal
Fault Tolerance: Principles and Practice
Fault Tolerance: Principles and Practice
Optimal Agreement Protocol in Malicious Faulty Processors and Faulty Links
IEEE Transactions on Knowledge and Data Engineering
Consensus With Dual Failure Modes
IEEE Transactions on Parallel and Distributed Systems
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
A New Approach for Byzantine Agreement
ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
Reaching Fault Diagnosis Agreement on Dual Link Failure Mode
ICPADS '00 Proceedings of the Seventh International Conference on Parallel and Distributed Systems
A flexible formal framework for masking/demasking faults
Information Sciences—Informatics and Computer Science: An International Journal
Reaching fault diagnosis agreement on an unreliable general network
Information Sciences—Informatics and Computer Science: An International Journal
Byzantine fault tolerant public key authentication in peer-to-peer systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
Optimally efficient multi-valued byzantine agreement
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
IEEE Transactions on Dependable and Secure Computing
IEEE Transactions on Computers
Streets of Byzantium: Network Architectures for Fast Reliable Broadcasts
IEEE Transactions on Software Engineering
Computer Standards & Interfaces
Byzantine Agreement under dual failure mobile network
Computer Standards & Interfaces
Discovering network topology in the presence of byzantine faults
SIROCCO'06 Proceedings of the 13th international conference on Structural Information and Communication Complexity
New directions in cryptography
IEEE Transactions on Information Theory
Securing reliable server pooling in MANET against byzantine adversaries
IEEE Journal on Selected Areas in Communications
Automatic identification of cardiac health using modeling techniques: A comparative study
Information Sciences: an International Journal
Accurate byzantine agreement with feedback
OPODIS'11 Proceedings of the 15th international conference on Principles of Distributed Systems
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Since 1982, numerous Byzantine Agreement Protocols (BAPs) have been developed to solve arbitrary faults in the Byzantine Generals Problem (BGP). A novel BAP, using an artificial neural network (ANN), was proposed by Wang and Kao. It requires message exchange rounds similar to the traditional BAP and its suitability, in the context of network size, has not been investigated. In the present study, we propose to adopt Nguyen-Widrow initialization in ANN training, which modifies message communication and limits the message exchange rounds to three rounds. This modified approach is referred to as BAP-ANN. The BAP-ANN performs better than the traditional BAP, when the network size n is greater than nine. We also evaluate the message exchange matrix (MEM) constructed during the message exchange stage. For a fixed number of faulty nodes and remainder cases of (n mod 3), the study shows that the mean epoch for ANN training decreases as the network size increases, which indicates better fault tolerance.