Simulate the effectiveness of various blockchain difficulty algorithms in terms of volatility and accuracy.
In a decentralized blockchain, where no individual controls the timing of block additions, there must be a mechanism set in place in order to regulate the desired block frequency.
A so-called 'difficulty algorithm' can be used to adjust the difficulty of mining a new block, based on an estimate of the network's total problem solving power. With all things being equal, the block time should approach and maintain its target block time.
The goal of this project is to provide a simulator to report on the effectiveness of various difficulty algorithms by observing the standard deviation, and mean values of all block intervals after adding X blocks.
Blockchain 1 SMA-10 SD: 18.598669175489476 Mean: 60.17482517482517
Blockchain 2 SMA-20 SD: 13.174972509226185 Mean: 59.324675324675326
Blockchain 3 SMA-50 SD: 13.718402628006942 Mean: 57.624375624375624
Blockchain 4 SMA-100 SD: 18.510401708827676 Mean: 55.07992007992008
Blockchain 5 EMA-10 SD: 18.598669175489476 Mean: 60.17482517482517
Blockchain 6 EMA-20 SD: 13.174972509226185 Mean: 59.324675324675326
Blockchain 7 EMA-50 SD: 13.718402628006942 Mean: 57.624375624375624
Blockchain 8 EMA-100 SD: 18.510401708827676 Mean: 55.07992007992008
Install Go: https://golang.org/doc/install
Download sources and install: go get github.com/seanvaleo/dsim
dsim
Configure environment variables in the .env file.
Default values:
TARGET_BLOCK_TIME=60
BLOCKS=1000
MINER_COUNT=100
MINER_HASH_TH=100