Add simulation of the avalanche consensus protocol to experimental (#3283)

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.idea/compiler.xml generated
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<module name="attachment-demo_integrationTest" target="1.8" />
<module name="attachment-demo_main" target="1.8" />
<module name="attachment-demo_test" target="1.8" />
<module name="avalanche_main" target="1.8" />
<module name="avalanche_test" target="1.8" />
<module name="bank-of-corda-demo_integrationTest" target="1.8" />
<module name="bank-of-corda-demo_main" target="1.8" />
<module name="bank-of-corda-demo_test" target="1.8" />

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# Avalanche Simulation
Experimental simulation of the Avalanche protocol by Team Rocket. This
implementation is incomplete.
The paper: [Snowflake to Avalanche: A Novel Metastable Consensus Protocol Family for
Cryptocurrencies](https://ipfs.io/ipfs/QmUy4jh5mGNZvLkjies1RWM4YuvJh5o2FYopNPVYwrRVGV).
## Running the Simulation
```
./gradlew shadowJar
java -jar build/libs/avalanche-all.jar --dump-dags
```
### Visualising the DAGs
```
for f in node-0-*.dot; do dot -Tpng -O $f; done
```
The above command generates a number of PNG files `node-0-*.png`, showing the
evolution of the DAG. The nodes are labeled with the ID of the spent state,
the chit and confidence values. The prefered transaction of a conflict set is
labelled with a star. Accepted transactions are blue.
![DAG](./images/node-0-003.dot.png)

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buildscript {
ext.kotlin_version = '1.2.40'
repositories {
mavenCentral()
jcenter()
}
dependencies {
classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
classpath 'com.github.jengelman.gradle.plugins:shadow:2.0.3'
}
}
plugins {
id "org.jetbrains.kotlin.jvm"
id 'com.github.johnrengelman.shadow' version '2.0.3'
id 'java'
id 'application'
}
repositories {
mavenCentral()
}
dependencies {
compile "org.jetbrains.kotlin:kotlin-stdlib-jdk8:$kotlin_version"
compile group: 'info.picocli', name: 'picocli', version: '3.0.1'
testCompile group: 'junit', name: 'junit', version: '4.12'
}
compileKotlin {
kotlinOptions {
jvmTarget = "1.8"
}
}
compileTestKotlin {
kotlinOptions {
jvmTarget = "1.8"
}
}
mainClassName = "net.corda.avalanche.MainKt"
shadowJar {
baseName = "avalanche"
}

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package net.corda.avalanche
import picocli.CommandLine
import java.io.File
import java.util.*
import kotlin.collections.LinkedHashMap
fun main(args: Array<String>) {
val parameters = Parameters()
CommandLine(parameters).parse(*args)
if (parameters.helpRequested) {
CommandLine.usage(Parameters(), System.out)
return
}
val network = Network(parameters)
val n1 = network.nodes[0]
val c1 = mutableListOf<Transaction>()
val c2 = mutableListOf<Transaction>()
repeat(parameters.nrTransactions) {
val n = network.nodes.shuffled(network.rng).first()
c1.add(n.onGenerateTx(it))
if (network.rng.nextDouble() < parameters.doubleSpendRatio) {
val d = network.rng.nextInt(it)
println("double spend of $d")
val n2 = network.nodes.shuffled(network.rng).first()
c2.add(n2.onGenerateTx(d))
}
network.run()
if (parameters.dumpDags) {
n1.dumpDag(File("node-0-${String.format("%03d", it)}.dot"))
}
println("$it: " + String.format("%.3f", fractionAccepted(n1)))
}
val conflictSets = (c1 + c2).groupBy { it.data }.filterValues { it.size > 1 }
conflictSets.forEach { v, txs ->
val acceptance = txs.map { t -> network.nodes.map { it.isAccepted(t) }.any { it } }
require(acceptance.filter { it }.size < 2) { "More than one transaction of the conflict set of $v got accepted." }
}
}
fun fractionAccepted(n: Node): Double {
val accepted = n.transactions.values.filter { n.isAccepted(it) }.size
return accepted.toDouble() / n.transactions.size
}
data class Transaction(
val id: UUID,
val data: Int,
val parents: List<UUID>,
var chit: Int = 0,
var confidence: Int = 0) {
override fun toString(): String {
return "T(id=${id.toString().take(5)}, data=$data, parents=[${parents.map {it.toString().take(5) }}, chit=$chit, confidence=$confidence)"
}
}
data class ConflictSet(
var pref: Transaction,
var last: Transaction,
var count: Int,
var size: Int
)
class Network(val parameters: Parameters) {
val rng = Random(parameters.seed)
val tx = Transaction(UUID.randomUUID(), -1, emptyList(), 1)
val nodes = (0..parameters.nrNodes).map { Node(it, parameters, tx.copy(),this, rng) }
fun run() {
nodes.forEach { it.avalancheLoop() }
}
}
class Node(val id: Int, parameters: Parameters, val genesisTx: Transaction, val network: Network, val rng: Random) {
val alpha = parameters.alpha
val k = parameters.k
val beta1 = parameters.beta1
val beta2 = parameters.beta2
val transactions = LinkedHashMap<UUID, Transaction>(mapOf(genesisTx.id to genesisTx))
val queried = mutableSetOf<UUID>(genesisTx.id)
val conflicts = mutableMapOf<Int, ConflictSet>(genesisTx.data to ConflictSet(genesisTx, genesisTx, 0, 1))
val accepted = mutableSetOf<UUID>(genesisTx.id)
val parentSets = mutableMapOf<UUID, Set<Transaction>>()
fun onGenerateTx(data: Int): Transaction {
val edges = parentSelection()
val t = Transaction(UUID.randomUUID(), data, edges.map { it.id })
onReceiveTx(this, t)
return t
}
fun onReceiveTx(sender: Node, tx: Transaction) {
if (transactions.contains(tx.id)) return
tx.chit = 0
tx.confidence = 0
tx.parents.forEach {
if (!transactions.contains(it)) {
val t = sender.onSendTx(it)
onReceiveTx(sender, t)
}
}
if (!conflicts.contains(tx.data)) {
conflicts[tx.data] = ConflictSet(tx, tx, 0, 1)
} else {
conflicts[tx.data]!!.size++
}
transactions[tx.id] = tx
}
fun onSendTx(id: UUID): Transaction {
return transactions[id]!!.copy()
}
fun onQuery(sender: Node, tx: Transaction): Int {
onReceiveTx(sender, tx)
return if (isStronglyPreferred(tx)) 1
else 0
}
fun avalancheLoop() {
val txs = transactions.values.filterNot { queried.contains(it.id) }
txs.forEach { tx ->
val sample = network.nodes.filterNot { it == this }.shuffled(rng).take(k)
val res = sample.map {
val txCopy = tx.copy()
it.onQuery(this, txCopy)
}.sum()
if (res >= alpha * k) {
tx.chit = 1
// Update the preference for ancestors.
parentSet(tx).forEach { p ->
p.confidence += 1
}
parentSet(tx).forEach { p->
val cs = conflicts[p.data]!!
if (p.confidence > cs.pref.confidence) {
cs.pref = p
}
if (p != cs.last) {
cs.last = p
cs.count = 0
} else {
cs.count++
}
}
}
queried.add(tx.id)
}
}
fun isPreferred(tx: Transaction): Boolean {
return conflicts[tx.data]!!.pref == tx
}
fun isStronglyPreferred(tx: Transaction): Boolean {
return parentSet(tx).map { isPreferred(it) }.all { it }
}
fun isAccepted(tx: Transaction): Boolean {
if (accepted.contains(tx.id)) return true
if (!queried.contains(tx.id)) return false
val cs = conflicts[tx.data]!!
val parentsAccepted = tx.parents.map { accepted.contains(it) }.all { it }
val isAccepted = (parentsAccepted && cs.size == 1 && tx.confidence > beta1) ||
(cs.pref == tx && cs.count > beta2)
if (isAccepted) accepted.add(tx.id)
return isAccepted
}
fun parentSet(tx: Transaction): Set<Transaction> {
if (parentSets.contains(tx.id)) return parentSets[tx.id]!!
val parents = mutableSetOf<Transaction>()
var ps = tx.parents.toSet()
while (ps.isNotEmpty()) {
ps.forEach {
if (transactions.contains(it)) parents.add(transactions[it]!!)
}
ps = ps.flatMap {
if (transactions.contains(it)) {
transactions[it]!!.parents
} else {
emptyList()
}
}.toSet()
}
parentSets[tx.id] = parents
return parents
}
fun parentSelection(): List<Transaction> {
val eps0 = transactions.values.filter { isStronglyPreferred(it) }
val eps1 = eps0.filter { conflicts[it.data]!!.size == 1 || it.confidence > 0 }
val parents = eps1.flatMap { parentSet(it) }.toSet().filterNot { eps1.contains(it) }
val fallback = if (transactions.size == 1) listOf(genesisTx)
else transactions.values.reversed().take(10).filter { !isAccepted(it) && conflicts[it.data]!!.size == 1 }.shuffled(network.rng).take(3)
require(parents.isNotEmpty() || fallback.isNotEmpty()) { "Unable to select parents." }
return if (parents.isEmpty()) return fallback else parents
}
fun dumpDag(f: File) {
f.printWriter().use { out ->
out.println("digraph G {")
transactions.values.forEach {
val color = if (isAccepted(it)) "color=lightblue; style=filled;" else ""
val pref = if (conflicts[it.data]!!.size > 1 && isPreferred(it)) "*" else ""
val chit = if (queried.contains(it.id)) it.chit.toString() else "?"
out.println("\"${it.id}\" [$color label=\"${it.data}$pref, $chit, ${it.confidence}\"];")
}
transactions.values.forEach {
it.parents.forEach { p->
out.println("\"${it.id}\" -> \"$p\";")
}
}
out.println("}")
}
}
}

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package net.corda.avalanche
import picocli.CommandLine
class Parameters {
@CommandLine.Option(names = ["-n", "--num-transactions"], description = ["How many transactions to generate (default: 20)"])
var nrTransactions: Int = 20
@CommandLine.Option(names = ["-d", "--double-spend-ratio"], description = ["The double spend ratio (default: 0.02)"])
var doubleSpendRatio: Double = 0.02
@CommandLine.Option(names = ["-a", "--alpha"], description = ["The alpha parameter (default: 0.8)"])
var alpha = 0.8
@CommandLine.Option(names = ["--num-nodes"], description = ["The number of nodes (default: 50)"])
var nrNodes = 50
@CommandLine.Option(names = ["-k", "--sample-size"], description = ["The sample size (default `1 + nrNodes / 10`)"])
var k = 1 + nrNodes / 10
@CommandLine.Option(names = ["--beta1"], description = ["The beta1 parameter (default: 5)"])
var beta1 = 5
@CommandLine.Option(names = ["--beta2"], description = ["The beta1 parameter (default: 5)"])
var beta2 = 5
@CommandLine.Option(names = ["-h", "--help"], usageHelp = true, description = ["Display help and exit"])
var helpRequested = false
@CommandLine.Option(names = ["--seed"], description = ["The RNG seed (default: 23)"])
var seed = 23L
@CommandLine.Option(names = ["--dump-dags"], description = ["Dump DAGs in dot format (default: false)"])
var dumpDags = false
@CommandLine.Option(names = ["-v", "--verbose"], description=["Verbose mode (default: false)"])
var verbose = false
}

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@ -16,6 +16,7 @@ include 'client:rpc'
include 'webserver'
include 'webserver:webcapsule'
include 'experimental'
include 'experimental:avalanche'
include 'experimental:behave'
include 'experimental:sandbox'
include 'experimental:quasar-hook'