def draw_extra4():
n = np.arange(10, 60, 10)
datas = [(n, 2 * n**2 - n - 1, 'kPBFT'), (n, n**2 + n * 3 - 2, '本协议')]
draw_plt(datas=datas,
xlabel='共识节点的数量',
ylabel='通信量',
mode='save',
save_name='node & communication')
def draw_extra3_1():
"""写链错误率对好写链比例的影响."""
MESSAGE_POOL_SIZE = 100
NODES = 30
ROUND = 50
P_N = 0.1
STRATEGY = 1
W = 5
P_WRITE_WRONG = np.arange(0.1, 0.5001, 0.05)
P_VOTE_WRONG = [0.2, 0.3, 0.4, 0.5]
res = {rate: dict() for rate in P_VOTE_WRONG}
for pvw in P_VOTE_WRONG:
print(f'P_VOTE_WRONG rate {pvw}')
for pww in P_WRITE_WRONG:
tmp = []
for _ in range(5):
bc = BlockChain(message_pool_size=MESSAGE_POOL_SIZE,
n=NODES,
p_n=P_N,
rd=ROUND,
strategy=STRATEGY,
w=W,
p_write_wrong=pww,
p_vote_wrong=pvw,
verbose=False)
write_stat = bc.start()
tmp.append(write_stat['bc_good_prob_in_append'])
res[pvw][pww] = np.mean(tmp)
# 绘制结果曲线
draw_plt(datas=[(res[k].keys(), res[k].values(), f'投票错误的概率={k}') for k in P_VOTE_WRONG],
xlabel='领导节点发布错误区块的概率',
ylabel='正确区块所占比例',
mode='save',
save_name='Block Chain pww & writerate')
def draw_extra1_1():
"""全节点转共识节点概率对上链比例的影响."""
MESSAGE_POOL_SIZE = 1000
NODES = 30
ROUND = [20, 50, 100]
P_N = np.arange(0.1, 1.01, 0.1)
STRATEGY = 1
W = 5
P_WRITE_WRONG = 0.2
P_VOTE_WRONG = 0.2
res = {rd: dict() for rd in ROUND}
for rd in ROUND:
print(f'Round {rd}')
for pn in P_N:
tmp = []
for _ in range(5):
bc = BlockChain(message_pool_size=MESSAGE_POOL_SIZE,
n=NODES,
p_n=pn,
rd=rd,
strategy=STRATEGY,
w=W,
p_write_wrong=P_WRITE_WRONG,
p_vote_wrong=P_VOTE_WRONG,
verbose=False)
write_stat = bc.start()
tmp.append(write_stat['bc_good_prob'])
res[rd][pn] = np.mean(tmp)
# 绘制结果曲线
draw_plt(datas=[(res[k].keys(), res[k].values(), f' ={k}') for k in ROUND],
xlabel='Probability of Consensus Nodes from Full Nodes',
ylabel='Good Write Probability',
mode='show',
save_name='Block Chain p_n & goodwriterate & round')
def draw3():
params = {
'message_pool_size': 10000,
'n': 60,
'rd': [2000, 5000, 10000],
'p_n': np.arange(0.1, 1.01, 0.1),
'strategy': 1,
'w': 5,
}
res = dict()
for rd in params['rd']:
res[rd] = dict()
for rd in params['rd']:
print('rd %d' % rd)
for p_n in params['p_n']:
p_n = round(p_n, 2)
tmp = []
for _ in range(5):
bc = BlockChain(message_pool_size=params['message_pool_size'],
n=params['n'],
p_n=p_n,
rd=rd,
strategy=params['strategy'],
w=params['w'],
verbose=False)
tmp.append(bc.start()['bc_size'])
res[rd][p_n] = np.mean(tmp) / (3 * params['n'] * p_n - 2)
# 绘制结果曲线
draw_plt(datas=[(res[k].keys(), res[k].values(), f'通信量={k}')
for k in [2000, 5000, 10000]],
xlabel='全节点的活跃度',
ylabel='领导节点产生的轮数',
mode='save',
save_name='Block Chain p_n & Leader Node Counts n=60')