109 lines
3.7 KiB
Python
109 lines
3.7 KiB
Python
# See https://stackoverflow.com/a/19521297/3187068
|
|
import matplotlib
|
|
matplotlib.use('pdf')
|
|
font = {'size': 8}
|
|
matplotlib.rc('font', **font)
|
|
|
|
from quorums import *
|
|
import datetime
|
|
import matplotlib.pyplot as plt
|
|
|
|
def main() -> None:
|
|
def seconds(x: int) -> datetime.timedelta:
|
|
return datetime.timedelta(seconds=x)
|
|
|
|
a = Node('a', write_capacity=2000, read_capacity=4000, latency=seconds(1))
|
|
b = Node('b', write_capacity=1000, read_capacity=2000, latency=seconds(1))
|
|
c = Node('c', write_capacity=2000, read_capacity=4000, latency=seconds(3))
|
|
d = Node('d', write_capacity=1000, read_capacity=2000, latency=seconds(4))
|
|
e = Node('e', write_capacity=2000, read_capacity=4000, latency=seconds(5))
|
|
fr = {
|
|
1.00: 0.,
|
|
0.90: 10.,
|
|
0.80: 20.,
|
|
0.70: 100.,
|
|
0.60: 100.,
|
|
0.50: 100.,
|
|
0.40: 60.,
|
|
0.30: 30.,
|
|
0.20: 30.,
|
|
0.10: 20.,
|
|
0.00: 0.,
|
|
}
|
|
|
|
maj = QuorumSystem(reads=majority([a, b, c, d, e]))
|
|
grid = QuorumSystem(reads=a*b + c*d*e)
|
|
paths = QuorumSystem(reads=a*b + a*c*e + d*e + d*c*b)
|
|
|
|
print('0-resilient Capacities')
|
|
print(maj.uniform_strategy().capacity(read_fraction=fr))
|
|
print(maj.capacity(read_fraction=fr))
|
|
print(grid.capacity(read_fraction=fr))
|
|
print(paths.capacity(read_fraction=fr))
|
|
print()
|
|
|
|
print('0-resilient Searched')
|
|
opt = search(nodes=[a, b, c, d, e],
|
|
resilience=1,
|
|
read_fraction=fr)
|
|
sigma = opt.strategy(read_fraction=fr)
|
|
print(opt)
|
|
print(sigma)
|
|
print(sigma.capacity(read_fraction=fr))
|
|
print()
|
|
|
|
for (sigma, name, filename, size) in [
|
|
(maj.uniform_strategy(), 'Majority Quorum System', 'majority_uniform', (3.25, 1.75)),
|
|
# (grid.strategy(read_fraction=fr), 'Grid Quorum System'),
|
|
(sigma, 'Searched Quorum System', 'searched', (3.25, 1.75)),
|
|
]:
|
|
fig, ax = plt.subplots(figsize=size)
|
|
plot_node_throughput_on(
|
|
ax,
|
|
sigma,
|
|
nodes = [a, b, c, d, e],
|
|
read_fraction=0.5,
|
|
)
|
|
ax.set_xlabel('Node')
|
|
ax.set_ylabel('Throughput')
|
|
fig.tight_layout()
|
|
fig.savefig(f'{filename}_throughputs.pdf')
|
|
|
|
print('1-resilient Capacities')
|
|
print(maj)
|
|
print(maj.capacity(read_fraction=fr, f=1))
|
|
print(grid.capacity(read_fraction=fr, f=1))
|
|
print(paths.capacity(read_fraction=fr, f=1))
|
|
print()
|
|
|
|
print('1-resilient Searched')
|
|
opt = search(nodes=[a, b, c, d, e], resilience=1, read_fraction=fr, f=1)
|
|
sigma = opt.strategy(read_fraction=fr, f=1)
|
|
print(opt)
|
|
print(sigma)
|
|
print(sigma.capacity(read_fraction=fr))
|
|
print()
|
|
|
|
print('Latency Optimal Capacities and Latencies')
|
|
print(maj.uniform_strategy().capacity(read_fraction=fr),
|
|
maj.uniform_strategy().latency(read_fraction=fr))
|
|
print(maj.capacity(read_fraction=fr, optimize='latency', load_limit=1/2000),
|
|
maj.latency(read_fraction=fr, optimize='latency', load_limit=1/2000))
|
|
print(grid.capacity(read_fraction=fr, optimize='latency', load_limit=1/2000),
|
|
grid.latency(read_fraction=fr, optimize='latency', load_limit=1/2000))
|
|
print(paths.capacity(read_fraction=fr, optimize='latency', load_limit=1/2000),
|
|
paths.latency(read_fraction=fr, optimize='latency', load_limit=1/2000))
|
|
print()
|
|
|
|
print('Latency Optimal Searched')
|
|
opt = search(nodes=[a, b, c, d, e], resilience=1, read_fraction=fr, optimize='latency', load_limit=1/2000)
|
|
sigma = opt.strategy(read_fraction=fr, optimize='latency', load_limit=1/2000)
|
|
print(opt)
|
|
print(sigma)
|
|
print(sigma.capacity(read_fraction=fr))
|
|
print(sigma.latency(read_fraction=fr))
|
|
print()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|