monero/tests/block_weight/block_weight.py
moneromooo-monero b8787f4302
ArticMine's new block weight algorithm
This curbs runaway growth while still allowing substantial
spikes in block weight

Original specification from ArticMine:

here is the scaling proposal
Define: LongTermBlockWeight
Before fork:
LongTermBlockWeight = BlockWeight
At or after fork:
LongTermBlockWeight = min(BlockWeight, 1.4*LongTermEffectiveMedianBlockWeight)
Note: To avoid possible consensus issues over rounding the LongTermBlockWeight for a given block should be calculated to the nearest byte, and stored as a integer in the block itself. The stored LongTermBlockWeight is then used for future calculations of the LongTermEffectiveMedianBlockWeight and not recalculated each time.
Define:   LongTermEffectiveMedianBlockWeight
LongTermEffectiveMedianBlockWeight = max(300000, MedianOverPrevious100000Blocks(LongTermBlockWeight))
Change Definition of EffectiveMedianBlockWeight
From (current definition)
EffectiveMedianBlockWeight  = max(300000, MedianOverPrevious100Blocks(BlockWeight))
To (proposed definition)
EffectiveMedianBlockWeight  = min(max(300000, MedianOverPrevious100Blocks(BlockWeight)), 50*LongTermEffectiveMedianBlockWeight)
Notes:
1) There are no other changes to the existing penalty formula, median calculation, fees etc.
2) There is the requirement to store the LongTermBlockWeight of a block unencrypted in the block itself. This  is to avoid possible consensus issues over rounding and also to prevent the calculations from becoming unwieldy as we move away from the fork.
3) When the  EffectiveMedianBlockWeight cap is reached it is still possible to mine blocks up to 2x the EffectiveMedianBlockWeight by paying the corresponding penalty.

Note: the long term block weight is stored in the database, but not in the actual block itself,
since it requires recalculating anyway for verification.
2019-03-04 09:33:58 +00:00

74 lines
2.4 KiB
Python
Executable file

#!/usr/bin/python
# Simulate a maximal block attack on the Monero network
# This uses the scheme proposed by ArticMine
# Written by Sarang Nother
# Copyright (c) 2019 The Monero Project
import sys
import math
MEDIAN_WINDOW_SMALL = 100 # number of recent blocks for median computation
MEDIAN_WINDOW_BIG = 5000
MULTIPLIER_SMALL = 1.4 # multipliers for determining weights
MULTIPLIER_BIG = 50.0
MEDIAN_THRESHOLD = 300*1000 # initial value for median (scaled kB -> B)
lcg_seed = 0
embw = MEDIAN_THRESHOLD
ltembw = MEDIAN_THRESHOLD
weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_SMALL # weights of recent blocks (B), with index -1 most recent
lt_weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_BIG # long-term weights
# Compute the median of a list
def get_median(vec):
#temp = vec
temp = sorted(vec)
if len(temp) % 2 == 1:
return temp[len(temp)/2]
else:
return int((temp[len(temp)/2]+temp[len(temp)/2-1])/2)
def LCG():
global lcg_seed
lcg_seed = (lcg_seed * 0x100000001b3 + 0xcbf29ce484222325) & 0xffffffff
return lcg_seed
def run(t, blocks):
global embw
global ltembw
weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_SMALL # weights of recent blocks (B), with index -1 most recent
lt_weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_BIG # long-term weights
for block in range(blocks):
# determine the long-term effective weight
ltmedian = get_median(lt_weights[-MEDIAN_WINDOW_BIG:])
ltembw = max(MEDIAN_THRESHOLD,ltmedian)
# determine the effective weight
stmedian = get_median(weights[-MEDIAN_WINDOW_SMALL:])
embw = min(max(MEDIAN_THRESHOLD,stmedian),int(MULTIPLIER_BIG*ltembw))
# drop the lowest values
weights = weights[1:]
lt_weights = lt_weights[1:]
# add a block of max weight
if t == 0:
max_weight = 2 * embw
elif t == 1:
r = LCG()
max_weight = int(90 + r % 500000 + 250000 + math.sin(block / 200.) * 350000)
if max_weight < 90: max_weight = 90
elif t == 2:
max_weight = 90
else:
sys.exit(1)
weights.append(max_weight)
lt_weights.append(min(max_weight,int(ltembw + int(ltembw * 2 / 5))))
#print "H %u, r %u, BW %u, EMBW %u, LTBW %u, LTEMBW %u, ltmedian %u" % (block, r, max_weight, embw, lt_weights[-1], ltembw, ltmedian)
print "H %u, BW %u, EMBW %u, LTBW %u" % (block, max_weight, embw, lt_weights[-1])
run(0, 2 * MEDIAN_WINDOW_BIG)
run(1, 9 * MEDIAN_WINDOW_BIG)
run(2, 1 * MEDIAN_WINDOW_BIG)