100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
"""
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This script contains the code used in our paper
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(https://mwhittaker.github.io/publications/quoracle.pdf).
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"""
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from quoracle import *
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import datetime
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def main() -> None:
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# The basics.
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a, b, c = Node('a'), Node('b'), Node('c')
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majority = QuorumSystem(reads=a*b + b*c + a*c)
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print(majority.resilience()) # 1
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print(majority.capacity(read_fraction=1)) # 1.5
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print()
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# Different capacities
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a, b = Node('a', capacity=100), Node('b', capacity=100)
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c, d = Node('c', capacity=50), Node('d', capacity=50)
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grid = QuorumSystem(reads=a*b + c*d)
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print(grid.capacity(read_fraction=1)) # 150
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print()
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# Different read and write capacities.
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a = Node('a', write_capacity=100, read_capacity=200)
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b = Node('b', write_capacity=100, read_capacity=200)
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c = Node('c', write_capacity=50, read_capacity=100)
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d = Node('d', write_capacity=50, read_capacity=100)
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grid = QuorumSystem(reads=a*b + c*d)
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print(grid.capacity(read_fraction=1)) # 300
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print(grid.capacity(read_fraction=0.5)) # 200
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print(grid.capacity(read_fraction=0)) # 100
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print()
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# Workload distribution.
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grid = QuorumSystem(reads=a*c + b*d)
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fr = {0.00: 10 / 18,
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0.25: 4 / 18,
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0.50: 2 / 18,
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0.75: 1 / 18,
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1.00: 1 / 18}
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print(grid.capacity(read_fraction=fr)) # 159
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print()
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# f-resilient strategies.
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grid = QuorumSystem(reads=a*b + c*d)
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choose2 = QuorumSystem(reads=choose(2, [a, b, c, d]))
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print(grid.capacity(read_fraction=1)) # 300
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print(choose2.capacity(read_fraction=1)) # 300
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print(grid.capacity(read_fraction=1, f=1)) # 100
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print(choose2.capacity(read_fraction=1, f=1)) # 200
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print(choose2.strategy(read_fraction=1, f=1)) # abd: 0.5, abc: 0.5
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print()
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# Network load and latency.
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def seconds(n: int) -> datetime.timedelta:
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return datetime.timedelta(seconds=n)
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a = Node('a', write_capacity=100, read_capacity=200, latency=seconds(4))
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b = Node('b', write_capacity=100, read_capacity=200, latency=seconds(4))
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c = Node('c', write_capacity=50, read_capacity=100, latency=seconds(1))
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d = Node('d', write_capacity=50, read_capacity=100, latency=seconds(1))
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grid = QuorumSystem(reads=a*b + c*d)
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sigma = grid.strategy(read_fraction=1)
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print(sigma.capacity(read_fraction=1)) # 300
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print(sigma.network_load(read_fraction=1)) # 2
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print(sigma.latency(read_fraction=1)) # 3 seconds
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print(grid.strategy(
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read_fraction = 1,
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optimize = 'latency',
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load_limit = 1 / 150,
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network_limit = 2,
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)) # ab: 1/3, cd: 2/3
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print()
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# Search.
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qs, sigma = search(
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nodes = [a, b, c, d],
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read_fraction = 1,
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optimize = 'latency',
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load_limit = 1 / 150,
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network_limit = 2,
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# timeout = seconds(3),
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)
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print(qs) # a + b + c + d
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# sigma = qs.strategy(
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# read_fraction = 1,
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# optimize = 'latency',
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# load_limit = 1 / 150,
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# network_limit = 2,
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# )
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print(sigma) # c: 1/3 d: 2/3
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print(sigma.capacity(read_fraction=1)) # 150
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print(sigma.network_load(read_fraction=1)) # 1
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print(sigma.latency(read_fraction=1)) # 1
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if __name__ == '__main__':
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main()
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