// Copyright 2017 Tendermint. All rights reserved.
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// Use of this source code is governed by Apache 2 LICENSE that can be found in the LICENSE file.
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package trust
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import (
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"math"
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"sync"
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"time"
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cmn "github.com/tendermint/tmlibs/common"
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)
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//---------------------------------------------------------------------------------------
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const (
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// The weight applied to the derivative when current behavior is >= previous behavior
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defaultDerivativeGamma1 = 0
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// The weight applied to the derivative when current behavior is less than previous behavior
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defaultDerivativeGamma2 = 1.0
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// The weight applied to history data values when calculating the history value
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defaultHistoryDataWeight = 0.8
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)
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// MetricHistoryJSON - history data necessary to save the trust metric
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type MetricHistoryJSON struct {
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NumIntervals int `json:"intervals"`
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History []float64 `json:"history"`
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}
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// TrustMetric - keeps track of peer reliability
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// See tendermint/docs/architecture/adr-006-trust-metric.md for details
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type TrustMetric struct {
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cmn.BaseService
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// Mutex that protects the metric from concurrent access
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mtx sync.Mutex
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// Determines the percentage given to current behavior
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proportionalWeight float64
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// Determines the percentage given to prior behavior
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integralWeight float64
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// Count of how many time intervals this metric has been tracking
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numIntervals int
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// Size of the time interval window for this trust metric
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maxIntervals int
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// The time duration for a single time interval
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intervalLen time.Duration
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// Stores the trust history data for this metric
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history []float64
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// Weights applied to the history data when calculating the history value
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historyWeights []float64
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// The sum of the history weights used when calculating the history value
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historyWeightSum float64
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// The current number of history data elements
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historySize int
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// The maximum number of history data elements
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historyMaxSize int
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// The calculated history value for the current time interval
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historyValue float64
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// The number of recorded good and bad events for the current time interval
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bad, good float64
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// While true, history data is not modified
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paused bool
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// Used during testing in order to control the passing of time intervals
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testTicker MetricTicker
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}
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// NewMetric returns a trust metric with the default configuration.
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// Use Start to begin tracking the quality of peer behavior over time
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func NewMetric() *TrustMetric {
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return NewMetricWithConfig(DefaultConfig())
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}
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// NewMetricWithConfig returns a trust metric with a custom configuration.
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// Use Start to begin tracking the quality of peer behavior over time
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func NewMetricWithConfig(tmc TrustMetricConfig) *TrustMetric {
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tm := new(TrustMetric)
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config := customConfig(tmc)
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// Setup using the configuration values
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tm.proportionalWeight = config.ProportionalWeight
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tm.integralWeight = config.IntegralWeight
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tm.intervalLen = config.IntervalLength
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// The maximum number of time intervals is the tracking window / interval length
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tm.maxIntervals = int(config.TrackingWindow / tm.intervalLen)
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// The history size will be determined by the maximum number of time intervals
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tm.historyMaxSize = intervalToHistoryOffset(tm.maxIntervals) + 1
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// This metric has a perfect history so far
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tm.historyValue = 1.0
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tm.BaseService = *cmn.NewBaseService(nil, "TrustMetric", tm)
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return tm
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}
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// OnStart implements Service
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func (tm *TrustMetric) OnStart() error {
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if err := tm.BaseService.OnStart(); err != nil {
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return err
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}
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go tm.processRequests()
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return nil
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}
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// OnStop implements Service
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// Nothing to do since the goroutine shuts down by itself via BaseService.Quit()
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func (tm *TrustMetric) OnStop() {}
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// Returns a snapshot of the trust metric history data
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func (tm *TrustMetric) HistoryJSON() MetricHistoryJSON {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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return MetricHistoryJSON{
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NumIntervals: tm.numIntervals,
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History: tm.history,
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}
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}
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// Instantiates a trust metric by loading the history data for a single peer.
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// This is called only once and only right after creation, which is why the
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// lock is not held while accessing the trust metric struct members
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func (tm *TrustMetric) Init(hist MetricHistoryJSON) {
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// Restore the number of time intervals we have previously tracked
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if hist.NumIntervals > tm.maxIntervals {
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hist.NumIntervals = tm.maxIntervals
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}
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tm.numIntervals = hist.NumIntervals
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// Restore the history and its current size
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if len(hist.History) > tm.historyMaxSize {
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// Keep the history no larger than historyMaxSize
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last := len(hist.History) - tm.historyMaxSize
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hist.History = hist.History[last:]
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}
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tm.history = hist.History
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tm.historySize = len(tm.history)
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// Create the history weight values and weight sum
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for i := 1; i <= tm.numIntervals; i++ {
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x := math.Pow(defaultHistoryDataWeight, float64(i)) // Optimistic weight
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tm.historyWeights = append(tm.historyWeights, x)
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}
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for _, v := range tm.historyWeights {
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tm.historyWeightSum += v
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}
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// Calculate the history value based on the loaded history data
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tm.historyValue = tm.calcHistoryValue()
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}
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// Pause tells the metric to pause recording data over time intervals.
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// All method calls that indicate events will unpause the metric
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func (tm *TrustMetric) Pause() {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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// Pause the metric for now
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tm.paused = true
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}
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// BadEvents indicates that an undesirable event(s) took place
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func (tm *TrustMetric) BadEvents(num int) {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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tm.unpause()
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tm.bad += float64(num)
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}
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// GoodEvents indicates that a desirable event(s) took place
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func (tm *TrustMetric) GoodEvents(num int) {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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tm.unpause()
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tm.good += float64(num)
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}
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// TrustValue gets the dependable trust value; always between 0 and 1
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func (tm *TrustMetric) TrustValue() float64 {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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return tm.calcTrustValue()
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}
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// TrustScore gets a score based on the trust value always between 0 and 100
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func (tm *TrustMetric) TrustScore() int {
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score := tm.TrustValue() * 100
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return int(math.Floor(score))
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}
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// NextTimeInterval saves current time interval data and prepares for the following interval
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func (tm *TrustMetric) NextTimeInterval() {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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if tm.paused {
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// Do not prepare for the next time interval while paused
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return
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}
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// Add the current trust value to the history data
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newHist := tm.calcTrustValue()
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tm.history = append(tm.history, newHist)
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// Update history and interval counters
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if tm.historySize < tm.historyMaxSize {
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tm.historySize++
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} else {
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// Keep the history no larger than historyMaxSize
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last := len(tm.history) - tm.historyMaxSize
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tm.history = tm.history[last:]
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}
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if tm.numIntervals < tm.maxIntervals {
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tm.numIntervals++
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// Add the optimistic weight for the new time interval
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wk := math.Pow(defaultHistoryDataWeight, float64(tm.numIntervals))
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tm.historyWeights = append(tm.historyWeights, wk)
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tm.historyWeightSum += wk
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}
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// Update the history data using Faded Memories
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tm.updateFadedMemory()
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// Calculate the history value for the upcoming time interval
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tm.historyValue = tm.calcHistoryValue()
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tm.good = 0
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tm.bad = 0
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}
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// SetTicker allows a TestTicker to be provided that will manually control
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// the passing of time from the perspective of the TrustMetric.
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// The ticker must be set before Start is called on the metric
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func (tm *TrustMetric) SetTicker(ticker MetricTicker) {
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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tm.testTicker = ticker
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}
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// Copy returns a new trust metric with members containing the same values
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func (tm *TrustMetric) Copy() *TrustMetric {
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if tm == nil {
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return nil
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}
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tm.mtx.Lock()
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defer tm.mtx.Unlock()
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return &TrustMetric{
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proportionalWeight: tm.proportionalWeight,
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integralWeight: tm.integralWeight,
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numIntervals: tm.numIntervals,
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maxIntervals: tm.maxIntervals,
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intervalLen: tm.intervalLen,
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history: tm.history,
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historyWeights: tm.historyWeights,
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historyWeightSum: tm.historyWeightSum,
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historySize: tm.historySize,
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historyMaxSize: tm.historyMaxSize,
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historyValue: tm.historyValue,
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good: tm.good,
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bad: tm.bad,
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paused: tm.paused,
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}
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}
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/* Private methods */
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// This method is for a goroutine that handles all requests on the metric
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func (tm *TrustMetric) processRequests() {
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t := tm.testTicker
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if t == nil {
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// No test ticker was provided, so we create a normal ticker
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t = NewTicker(tm.intervalLen)
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}
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defer t.Stop()
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// Obtain the raw channel
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tick := t.GetChannel()
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loop:
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for {
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select {
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case <-tick:
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tm.NextTimeInterval()
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case <-tm.Quit():
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// Stop all further tracking for this metric
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break loop
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}
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}
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}
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// Wakes the trust metric up if it is currently paused
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// This method needs to be called with the mutex locked
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func (tm *TrustMetric) unpause() {
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// Check if this is the first experience with
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// what we are tracking since being paused
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if tm.paused {
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tm.good = 0
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tm.bad = 0
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// New events cause us to unpause the metric
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tm.paused = false
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}
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}
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// Calculates the trust value for the request processing
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func (tm *TrustMetric) calcTrustValue() float64 {
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weightedP := tm.proportionalWeight * tm.proportionalValue()
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weightedI := tm.integralWeight * tm.historyValue
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weightedD := tm.weightedDerivative()
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tv := weightedP + weightedI + weightedD
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// Do not return a negative value.
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if tv < 0 {
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tv = 0
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}
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return tv
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}
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// Calculates the current score for good/bad experiences
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func (tm *TrustMetric) proportionalValue() float64 {
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value := 1.0
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total := tm.good + tm.bad
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if total > 0 {
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value = tm.good / total
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}
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return value
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}
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// Strengthens the derivative component when the change is negative
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func (tm *TrustMetric) weightedDerivative() float64 {
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var weight float64 = defaultDerivativeGamma1
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d := tm.derivativeValue()
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if d < 0 {
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weight = defaultDerivativeGamma2
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}
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return weight * d
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}
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// Calculates the derivative component
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func (tm *TrustMetric) derivativeValue() float64 {
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return tm.proportionalValue() - tm.historyValue
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}
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// Calculates the integral (history) component of the trust value
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func (tm *TrustMetric) calcHistoryValue() float64 {
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var hv float64
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for i := 0; i < tm.numIntervals; i++ {
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hv += tm.fadedMemoryValue(i) * tm.historyWeights[i]
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}
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return hv / tm.historyWeightSum
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}
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// Retrieves the actual history data value that represents the requested time interval
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func (tm *TrustMetric) fadedMemoryValue(interval int) float64 {
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first := tm.historySize - 1
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if interval == 0 {
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// Base case
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return tm.history[first]
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}
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offset := intervalToHistoryOffset(interval)
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return tm.history[first-offset]
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}
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// Performs the update for our Faded Memories process, which allows the
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// trust metric tracking window to be large while maintaining a small
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// number of history data values
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func (tm *TrustMetric) updateFadedMemory() {
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if tm.historySize < 2 {
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return
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}
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end := tm.historySize - 1
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// Keep the most recent history element
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for count := 1; count < tm.historySize; count++ {
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i := end - count
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// The older the data is, the more we spread it out
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x := math.Pow(2, float64(count))
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// Two history data values are merged into a single value
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tm.history[i] = ((tm.history[i] * (x - 1)) + tm.history[i+1]) / x
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}
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}
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// Map the interval value down to an offset from the beginning of history
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func intervalToHistoryOffset(interval int) int {
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// The system maintains 2^m interval values in the form of m history
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// data values. Therefore, we access the ith interval by obtaining
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// the history data index = the floor of log2(i)
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return int(math.Floor(math.Log2(float64(interval))))
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}
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