mirror of
https://github.com/logos-blockchain/logos-blockchain-simulations.git
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91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
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import math
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import typer
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from scipy.stats import binom
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CARNOT_ADVERSARY_THRESHOLD_PER_COMMITTEE: float = 1/3
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CARNOT_NETWORK_ADVERSARY_THRESHOLD: float = 1 / 4
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def compute_optimal_number_of_committees_and_committee_size(
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number_of_nodes: int,
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failure_threshold: float,
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adversaries_threshold_per_committee: float,
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network_adversary_threshold: float
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):
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assert failure_threshold > 0
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# number_of_nodes is the number of nodes in the network
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# failure_threshold is the prob. of failure which can be tolerated
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# adversaries_threshold_per_committee is the fraction of Byzantine modes in a committee
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# network_adversary_threshold is the fraction of Byzantine nodes in the network
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number_of_committees = 1
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committee_size = number_of_nodes
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remainder = 0
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current_probability = 0.0
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odd_committee = 0
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while current_probability < failure_threshold:
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previous_number_of_committees = number_of_committees
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previous_committee_size = committee_size
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previous_remainder = remainder
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previous_probability = current_probability
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odd_committee = odd_committee + 1
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number_of_committees = 2 * odd_committee + 1
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committee_size = number_of_nodes // number_of_committees
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remainder = number_of_nodes % number_of_committees
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committee_size_probability = binom.cdf(
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math.floor(adversaries_threshold_per_committee * committee_size),
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committee_size,
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network_adversary_threshold
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)
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if 0 < remainder:
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committee_size_plus_one_probability = binom.cdf(
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math.floor(adversaries_threshold_per_committee * (committee_size + 1)),
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committee_size + 1,
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network_adversary_threshold
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)
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current_probability = (
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1 - committee_size_probability ** (number_of_committees - remainder)
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* committee_size_plus_one_probability ** remainder
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)
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else:
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current_probability = 1 - committee_size_probability ** number_of_committees
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# return the number_of_committees, committee_size, remainder and current_probability
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# computed at the previous iteration.
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return previous_number_of_committees, previous_committee_size, previous_remainder, previous_probability
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def main(ctx: typer.Context,
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num_nodes: int = typer.Option(1024,
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help="Set the number of nodes",),
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failure_threshold: float = typer.Option(0.5,
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help="Set the failure probability")
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):
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num_comm, comm_size, remainder, prob = compute_optimal_number_of_committees_and_committee_size(
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num_nodes,
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failure_threshold,
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CARNOT_ADVERSARY_THRESHOLD_PER_COMMITTEE,
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CARNOT_NETWORK_ADVERSARY_THRESHOLD)
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tree_depth= math.ceil(math.log(num_comm, 2)) if num_comm > 1 else 1
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num_nodes_branch= tree_depth * comm_size
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print(
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f"num_nodes={num_nodes}, "
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f"total_tree_nodes={num_comm}, comm_size={comm_size}, remainder={remainder}, computed={prob:f}(req={failure_threshold:f}), depth={tree_depth}"
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)
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tree_spec = f"tree,{num_nodes},{comm_size},"
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branch_spec = f"branch,{num_nodes_branch},{tree_depth},"
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print(tree_spec)
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print(branch_spec)
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if __name__ == "__main__":
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typer.run(main)
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