mirror of
https://github.com/openziti/ziti.git
synced 2026-09-10 08:45:41 +00:00
Paul Lorenz
94 lines
2.3 KiB
Go
94 lines
2.3 KiB
Go
/*
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Copyright NetFoundry Inc.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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https://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package xt_weighted
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import (
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"math/rand"
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"time"
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"github.com/openziti/ziti/v2/controller/xt"
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"github.com/openziti/ziti/v2/controller/xt_common"
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)
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/**
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The weighted strategy does random selection of available strategies in proportion to the terminator costs. So if a
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given terminator has twice the fully evaluated cost as another terminator it should ideally be selected roughly half
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as often.
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*/
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func NewFactory() xt.Factory {
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return &factory{}
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}
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type factory struct{}
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func (self *factory) GetStrategyName() string {
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return "weighted"
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}
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func (self *factory) NewStrategy() xt.Strategy {
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strategy := &strategy{
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CostVisitor: *xt_common.NewCostVisitor(2, 20, 2),
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}
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strategy.CreditOverTimeExponential(time.Minute, 5*time.Minute)
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return strategy
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}
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type strategy struct {
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xt_common.CostVisitor
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}
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func (self *strategy) Select(_ xt.CreateCircuitParams, terminators []xt.CostedTerminator) (xt.CostedTerminator, xt.PeerData, error) {
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terminators = xt.GetRelatedTerminators(terminators)
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if len(terminators) == 1 {
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return terminators[0], nil, nil
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}
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var costIdx []float32
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totalCost := float32(0)
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for _, t := range terminators {
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unbiasedCost := float32(t.GetPrecedence().Unbias(t.GetRouteCost()))
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if unbiasedCost == 0 {
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unbiasedCost = 1
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}
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costIdx = append(costIdx, unbiasedCost)
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totalCost += unbiasedCost
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}
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totalWeight := float32(0)
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for idx, cost := range costIdx {
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weight := 1 - (cost / totalCost)
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costIdx[idx] = weight
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totalWeight += weight
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}
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cumulative := float32(0)
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for idx, weight := range costIdx {
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cumulative += weight / totalWeight
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costIdx[idx] = cumulative
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}
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selected := rand.Float32()
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for idx, cost := range costIdx {
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if selected < cost {
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return terminators[idx], nil, nil
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}
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}
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return terminators[0], nil, nil
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}
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