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Could this be modelled with a geometric distribution? If we see the probability of success (termination in a specific round) as the probability of picking all the same bits (all 0s or all 1s) in the coin flip step? |
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I asked BingAI and he wrote this, what do you think? The Ben-Or randomized consensus algorithm is a fundamental algorithm in distributed computing, designed to solve consensus in an asynchronous message-passing system where processes can fail by crashing. In the specific case, where there are 5 processes and up to 2 can fail, the algorithm can still reach consensus if a majority of processes are correct. However, the termination of the algorithm is probabilistic, and it’s not guaranteed to terminate in a fixed number of rounds. The probability of termination after |
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The variable The probability
Since |
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How can |
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If there are no failures the system with 5 participants will always reach a majority either on '0' or '1' on the first round. |
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Consider an asynchronous system of 5 processes that run the Ben-Or randomized consensus algorithm. The number of failures that the system allows is 2. Show that, if at 2 failures occurs, then the probability that the protocol terminates after$x$ rounds is smaller than $\alpha^x$ , for some $\alpha$ .
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