Resource Management for Resource Management for Real-Time EnvironmentsReal-Time Environments

Instructor: Dr. Subra GanesanInstructor: Dr. Subra Ganesan

Presented by: Pooja MehtaPresented by: Pooja Mehta

Date: 10/16/06Date: 10/16/06

Presentation outlinePresentation outline

MotivationMotivation

Problem illustrations of Radar systemsProblem illustrations of Radar systems– Basic Radar modelBasic Radar model– Tasks with Harmonic PeriodsTasks with Harmonic Periods– Offline Template GenerationOffline Template Generation– Schedule construction on HyperperiodSchedule construction on Hyperperiod

Some Proposed SolutionsSome Proposed Solutions– Feasible IntervalsFeasible Intervals– Online Template GenerationOnline Template Generation– Finite Horizon SchedulingFinite Horizon Scheduling

ConclusionsConclusions

MotivationMotivation

The traditional notion of real-time systemsThe traditional notion of real-time systems

0 T1 2T1

3T1

0 T2 2T2

3T2

4T2

TASK 1

TASK 2

Periodic tasks Known periodsKnown execution timesKnown deadlines

However, many important applications lack this simple However, many important applications lack this simple structurestructure

Complexity arises because ofComplexity arises because of– Stringent task requirementsStringent task requirements– Scale of systemsScale of systems

Presentation outlinePresentation outline

MotivationMotivation

Problem illustrations of Radar systemsProblem illustrations of Radar systems– Basic Radar modelBasic Radar model– Tasks with Harmonic PeriodsTasks with Harmonic Periods– Offline Template GenerationOffline Template Generation– Schedule construction on HyperperiodSchedule construction on Hyperperiod

Some Proposed SolutionsSome Proposed Solutions– Feasible IntervalsFeasible Intervals– Online Template GenerationOnline Template Generation– Finite Horizon SchedulingFinite Horizon Scheduling

ConclusionsConclusions

Basic Radar ModelBasic Radar Model

Ai : Transmit Power

txi : Transmit pulse width

twi: Wait time

tri : Receive time

Radar System Model

Processing requirements for radar Processing requirements for radar taskstasks

Signals received at the antenna need to be processed Signals received at the antenna need to be processed (backend computations)(backend computations)– At multiple stagesAt multiple stages– Within an end-to-end deadlineWithin an end-to-end deadline

FILTERING CLASSIFICATIONCOMMAND

GENERATION

End-to-end deadline

Execution requirements on each node

Radar dwell schedulingRadar dwell scheduling

Nth job

(N+1)th job

Illumination windowLast

illumination time

Temporal distance

Processing window

Radar dwell schedulingRadar dwell scheduling

Non-preemptible

Reusable

Radar dwell

Question: How do we schedule many such tasks?

Constraints on power

Dwell packing

Power (kw)

t

P(t)τxt

e

Template-based ScheduleTemplate-based Schedule

Q-RAM & Scheduler Admission ControlQ-RAM & Scheduler Admission Control

• Reduce the resource utilization bounds

• Changes at irregular intervals

Offline Template GenerationOffline Template Generation

Offline Template GenerationOffline Template Generation

task types were restricted to a finite settask types were restricted to a finite set

appropriate templates were chosen during online appropriate templates were chosen during online operationoperation

Resource managers could only pick task types from Resource managers could only pick task types from the finite set.the finite set.

Presentation outlinePresentation outline

MotivationMotivation

Problem illustrations of Radar systemsProblem illustrations of Radar systems– Basic Radar modelBasic Radar model– Tasks with Harmonic PeriodsTasks with Harmonic Periods– Offline Template GenerationOffline Template Generation– Schedule construction on HyperperiodSchedule construction on Hyperperiod

Some Proposed SolutionsSome Proposed Solutions– Feasible IntervalsFeasible Intervals– Online Template GenerationOnline Template Generation– Finite Horizon SchedulingFinite Horizon Scheduling

ConclusionsConclusions

Dynamic Q-RAM OptimizationDynamic Q-RAM Optimization

Online Template GenerationOnline Template Generation

Arbitrary tasks can be interleaved or nested on-the-fly.

Online Template GenerationOnline Template Generation

arbitrary task types can be combined on-the-fly to arbitrary task types can be combined on-the-fly to produce a template; produce a template;

provides greater freedom to a resource manager. provides greater freedom to a resource manager.

The resource manager can tune the parameters of each The resource manager can tune the parameters of each task with finer granularity. task with finer granularity.

Online template generation is carried out using a fast Online template generation is carried out using a fast heuristic based on task characteristics.heuristic based on task characteristics.

Resource management frameworkResource management framework

Radar dwell scheduling – issuesRadar dwell scheduling – issues

Non-preemptible

Constraints on power

Dwell packing

Temporal distance constraints

Dwell scheduling – solutionsDwell scheduling – solutions

Fixed length templates for packing dwellsHeuristics for building templates

Template length divides the smallest period

Temporal distance

Synthetic period

Feasible intervals

Modular Schedule UpdatesModular Schedule Updates

Without modular schedule update

With modular schedule update

ConstraintsConstraints

Temporal ConstraintsTemporal ConstraintsWhen new tasks are admitted, the schedule changes only within the When new tasks are admitted, the schedule changes only within the templates in which new jobs are inserted. templates in which new jobs are inserted.

Energy ConstraintsEnergy Constraints Since a job is inserted into a template only if it will not cause the energy Since a job is inserted into a template only if it will not cause the energy

level to exceed level to exceed ETHETH, and since job insertions assume that the energy level , and since job insertions assume that the energy level at the start of a template is at the start of a template is ETHETH, job insertions are guaranteed to be safe in , job insertions are guaranteed to be safe in terms of the energy constraint. terms of the energy constraint.

Dealing with the energy Dealing with the energy constraintconstraint

Cooldown timeCooldown time

ETH

Cool-down durationfor Dwell A

Cool-down durationfor Dwell B

L

Finite horizon schedulingFinite horizon scheduling

A A A A A

T T+H

Task B arrives; is rejected

Task A departs

Feasible intervals for Task B

Task B need not have been rejected

horizon

Scheduling overheadScheduling overhead

Scheduling overhead

0

200

400

600

800

1000

1200

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8

Probability of track confirmation

Inse

rtio

n tim

e/ta

sk (m s)

Finite Horizon

Hyperperiod

Reduced task rejection ratesReduced task rejection rates

Comparing rejection rates

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Probability of track confirmation

Rej

ectio

n r

ate

Hyperperiod

Finite Horizon

Utilization improvementUtilization improvement

Comparing utilization

0

0.1

0.2

0.3

0.4

0.5

0.6

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8Probability of track confirmation

Util

izatio

n

Hyperperiod

Finite Horizon

Maximum achievable with energy bound

Presentation outlinePresentation outline

MotivationMotivation

Problem illustrations of Radar systemsProblem illustrations of Radar systems– Basic Radar modelBasic Radar model– Tasks with Harmonic PeriodsTasks with Harmonic Periods– Offline Template GenerationOffline Template Generation– Schedule construction on HyperperiodSchedule construction on Hyperperiod

Some Proposed SolutionsSome Proposed Solutions– Feasible IntervalsFeasible Intervals– Online Template GenerationOnline Template Generation– Finite Horizon SchedulingFinite Horizon Scheduling

ConclusionsConclusions

ConclusionsConclusions

All Real time systems doesn’t follow Ideal modelAll Real time systems doesn’t follow Ideal model

Determination of Schedulability RegionsDetermination of Schedulability Regions

Knowing the Schedule not just the schedulabilityKnowing the Schedule not just the schedulability

Systems should be able to handle unseen tasks, Systems should be able to handle unseen tasks, without violating the Temporal and Energy without violating the Temporal and Energy constraintsconstraints

ReferencesReferences[1] C.-S. Shih, S. Gopalakrishnan, P. Ganti, M. Caccamo, L. Sha: “Template-

based real-time dwell scheduling with energy constraint,” IEEE Real-Time Technology and Applications Symposium, Washington D.C., USA, May 2003.

[2] C.-S. Shih, S. Gopalakrishnan, P. Ganti, M. Caccamo, L.Sha: “Scheduling real-time dwells using tasks withsynthetic periods,” IEEE Real-Time Systems Symposium, Cancun, Mexico, December 2003.

[3] C.-G. Lee, P.-S. Kang, C.-S. Shih, L. Sha: “Radar dwell scheduling considering physical characteristics of phased array antenna,” IEEE Real-Time Systems Symposium,Cancun, Mexico, December 2003.

[4] J. Hansen, S. Ghosh, R. Rajkumar, J. Lehoczky: “Resource management of highly configurable tasks,” Workshop on Parallel and Distributed Real-Time Systems, Santa Fe, USA, April 2004.

References Contd..References Contd..

[5] MURI on QoS in Surveillance and Control Radar Dwell Scheduling for Phased-Array Radars PIs Lui Sha Marco Caccamo Chang-Gun Lee

[6] GOPALAKRISHNAN, S. Resource Management for Real-Time Environments. PhD thesis, University of Illinois, Urbana, Illinois, Dec. 2005.

[7] GOPALAKRISHNAN, S., CACCAMO, M., SHIH, C.-S., SHA, L., AND LEE, C.-G. Finite horizon scheduling of radar dwells with online template construction. Real-Time Systems (2006).

Thank you !!!!Thank you !!!!

Questions and AnswersQuestions and Answers