Merged in measureClassificationOverhead (pull request #12)
MeasureClassificationOverhead Approved-by: Akash Kothawale <akothaw1@binghamton.edu>
This commit is contained in:
Pradyumna Kaushik
parent
ae81125110
commit
f1c6adb05b
9 changed files with 127 additions and 81 deletions
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@ -404,3 +404,8 @@ func (s *BaseScheduler) LogSchedPolicySwitch(taskDist float64, name string, next
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s.Log(elecLogDef.GENERAL, fmt.Sprintf("Switching... TaskDistribution[%d] ==> %s", taskDist, name))
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}
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}
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func (s *BaseScheduler) LogClsfnAndTaskDistOverhead(overhead time.Duration) {
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// Logging the overhead in microseconds.
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s.Log(elecLogDef.CLSFN_TASKDIST_OVERHEAD, fmt.Sprintf("%f", float64(overhead.Nanoseconds())/1000.0))
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}
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@ -5,6 +5,7 @@ import (
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elecLogDef "bitbucket.org/sunybingcloud/elektron/logging/def"
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mesos "github.com/mesos/mesos-go/api/v0/mesosproto"
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sched "github.com/mesos/mesos-go/api/v0/scheduler"
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"time"
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)
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// Implements mesos scheduler.
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@ -72,4 +73,6 @@ type ElectronScheduler interface {
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LogTaskStatusUpdate(status *mesos.TaskStatus)
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// Log Scheduling policy switches (if any)
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LogSchedulingPolicySwitch()
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// Log the computation overhead of classifying tasks in the scheduling window.
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LogClsfnAndTaskDistOverhead(overhead time.Duration)
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}
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@ -6,7 +6,6 @@ import (
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"bitbucket.org/sunybingcloud/elektron/utilities/offerUtils"
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mesos "github.com/mesos/mesos-go/api/v0/mesosproto"
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sched "github.com/mesos/mesos-go/api/v0/scheduler"
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"log"
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)
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// Decides if to take an offer or not
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@ -4,6 +4,7 @@ import (
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"bitbucket.org/sunybingcloud/electron/def"
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mesos "github.com/mesos/mesos-go/api/v0/mesosproto"
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sched "github.com/mesos/mesos-go/api/v0/scheduler"
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"time"
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)
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type SchedPolicyContext interface {
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@ -46,69 +47,77 @@ func (bsps *baseSchedPolicyState) SwitchIfNecessary(spc SchedPolicyContext) {
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// The next scheduling policy will schedule at max schedWindowSize number of tasks.
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baseSchedRef.schedWindowSize, baseSchedRef.numTasksInSchedWindow =
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baseSchedRef.schedWindowResStrategy.Apply(func() interface{} { return baseSchedRef.tasks })
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// Determine the distribution of tasks in the new scheduling window.
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taskDist, err := def.GetTaskDistributionInWindow(baseSchedRef.schedWindowSize, baseSchedRef.tasks)
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// If no resource offers have been received yet, and
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// the name of the first scheduling policy to be deployed is provided,
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// we switch to this policy regardless of the task distribution.
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if !baseSchedRef.hasReceivedResourceOffers && (baseSchedRef.nameOfFstSchedPolToDeploy != "") {
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switchToPolicyName = baseSchedRef.nameOfFstSchedPolToDeploy
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} else if err != nil {
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// All the tasks in the window were only classified into 1 cluster.
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// Max-Min and Max-GreedyMins would work the same way as Bin-Packing for this situation.
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// So, we have 2 choices to make. First-Fit or Bin-Packing.
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// If choose Bin-Packing, then there might be a performance degradation due to increase in
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// resource contention. So, First-Fit might be a better option to cater to the worst case
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// where all the tasks are power intensive tasks.
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// TODO: Another possibility is to do the exact opposite and choose Bin-Packing.
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// TODO[2]: Determine scheduling policy based on the distribution of tasks in the whole queue.
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switchToPolicyName = bp
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} else {
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// The tasks in the scheduling window were classified into 2 clusters, meaning that there is
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// some variety in the kind of tasks.
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// We now select the scheduling policy which is most appropriate for this distribution of tasks.
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first := schedPoliciesToSwitch[0]
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last := schedPoliciesToSwitch[len(schedPoliciesToSwitch)-1]
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if taskDist < first.sp.GetInfo().taskDist {
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switchToPolicyName = first.spName
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} else if taskDist > last.sp.GetInfo().taskDist {
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switchToPolicyName = last.spName
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if baseSchedRef.schedWindowSize > 0 {
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// Record overhead to classify the tasks in the scheduling window and using the classification results
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// to determine the distribution of low power consuming and high power consuming tasks.
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startTime := time.Now()
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// Determine the distribution of tasks in the new scheduling window.
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taskDist, err := def.GetTaskDistributionInWindow(baseSchedRef.schedWindowSize, baseSchedRef.tasks)
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baseSchedRef.LogClsfnAndTaskDistOverhead(time.Now().Sub(startTime))
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// If no resource offers have been received yet, and
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// the name of the first scheduling policy to be deployed is provided,
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// we switch to this policy regardless of the task distribution.
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if !baseSchedRef.hasReceivedResourceOffers && (baseSchedRef.nameOfFstSchedPolToDeploy != "") {
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switchToPolicyName = baseSchedRef.nameOfFstSchedPolToDeploy
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} else if err != nil {
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// All the tasks in the window were only classified into 1 cluster.
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// Max-Min and Max-GreedyMins would work the same way as Bin-Packing for this situation.
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// So, we have 2 choices to make. First-Fit or Bin-Packing.
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// If choose Bin-Packing, then there might be a performance degradation due to increase in
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// resource contention. So, First-Fit might be a better option to cater to the worst case
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// where all the tasks are power intensive tasks.
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// TODO: Another possibility is to do the exact opposite and choose Bin-Packing.
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// TODO[2]: Determine scheduling policy based on the distribution of tasks in the whole queue.
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switchToPolicyName = bp
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} else {
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low := 0
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high := len(schedPoliciesToSwitch) - 1
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for low <= high {
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mid := (low + high) / 2
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if taskDist < schedPoliciesToSwitch[mid].sp.GetInfo().taskDist {
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high = mid - 1
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} else if taskDist > schedPoliciesToSwitch[mid].sp.GetInfo().taskDist {
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low = mid + 1
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} else {
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switchToPolicyName = schedPoliciesToSwitch[mid].spName
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break
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// The tasks in the scheduling window were classified into 2 clusters, meaning that there is
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// some variety in the kind of tasks.
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// We now select the scheduling policy which is most appropriate for this distribution of tasks.
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first := schedPoliciesToSwitch[0]
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last := schedPoliciesToSwitch[len(schedPoliciesToSwitch)-1]
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if taskDist < first.sp.GetInfo().taskDist {
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switchToPolicyName = first.spName
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} else if taskDist > last.sp.GetInfo().taskDist {
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switchToPolicyName = last.spName
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} else {
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low := 0
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high := len(schedPoliciesToSwitch) - 1
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for low <= high {
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mid := (low + high) / 2
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if taskDist < schedPoliciesToSwitch[mid].sp.GetInfo().taskDist {
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high = mid - 1
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} else if taskDist > schedPoliciesToSwitch[mid].sp.GetInfo().taskDist {
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low = mid + 1
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} else {
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switchToPolicyName = schedPoliciesToSwitch[mid].spName
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break
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}
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}
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}
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// We're here if low == high+1.
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// If haven't yet found the closest match.
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if switchToPolicyName == "" {
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lowDiff := schedPoliciesToSwitch[low].sp.GetInfo().taskDist - taskDist
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highDiff := taskDist - schedPoliciesToSwitch[high].sp.GetInfo().taskDist
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if lowDiff > highDiff {
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switchToPolicyName = schedPoliciesToSwitch[high].spName
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} else if highDiff > lowDiff {
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switchToPolicyName = schedPoliciesToSwitch[low].spName
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} else {
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// index doens't matter as the values at high and low are equidistant
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// from taskDist.
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switchToPolicyName = schedPoliciesToSwitch[high].spName
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// We're here if low == high+1.
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// If haven't yet found the closest match.
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if switchToPolicyName == "" {
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lowDiff := schedPoliciesToSwitch[low].sp.GetInfo().taskDist - taskDist
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highDiff := taskDist - schedPoliciesToSwitch[high].sp.GetInfo().taskDist
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if lowDiff > highDiff {
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switchToPolicyName = schedPoliciesToSwitch[high].spName
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} else if highDiff > lowDiff {
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switchToPolicyName = schedPoliciesToSwitch[low].spName
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} else {
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// index doens't matter as the values at high and low are equidistant
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// from taskDist.
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switchToPolicyName = schedPoliciesToSwitch[high].spName
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}
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}
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}
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}
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// Switching scheduling policy.
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baseSchedRef.LogSchedPolicySwitch(taskDist, switchToPolicyName, SchedPolicies[switchToPolicyName])
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baseSchedRef.SwitchSchedPol(SchedPolicies[switchToPolicyName])
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// Resetting the number of tasks scheduled.
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bsps.numTasksScheduled = 0
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} else {
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// There is no need to switch the scheduling policy as there aren't any tasks in the window.
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}
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// Switching scheduling policy.
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baseSchedRef.LogSchedPolicySwitch(taskDist, switchToPolicyName, SchedPolicies[switchToPolicyName])
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baseSchedRef.SwitchSchedPol(SchedPolicies[switchToPolicyName])
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// Resetting the number of tasks scheduled.
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bsps.numTasksScheduled = 0
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}
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}
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