The Real-Time Execution Performance Agent

Sam Siewertsiewerts@rodin.colorado.edu

An Hard/Soft Real-Time Digital Control and Continuous MediaExperiment to Demonstrate Confidence-Based Scheduling

With The RT-EPA Execution Control Interface

Motivation for RT-EPA

• Emerging Soft Real-Time Applications– Virtual Reality, Multimedia, Flexible Automation and Control

• Device Interfaces with RT Processing Between Them– Range of Device Bandwidths and Characteristics

Aperiodic Bursty Periodic

– Range of RT Performance Reliability Required

Best-Effort Confidence-Based Guaranteed

• Negotiated Service & Control of Kernel Processing Pipelines– Kernel Pipeline Efficiency Well-Demonstrated (Fall & Govindan)

– Use Real-Time Kernel Threads and Provide Trades between Utilization and Expected Number of Deadline Misses

Problems Addressed and Approach

• “Soft” Real-Time - Confidence-Based Scheduling– Not Guaranteed, Not Best Effort -- Probabilistic Predictability

– Can Deadline Confidence Be Derived from Execution Time Confidence? -- Deadline Monotonic Confidence Extension

– Can WCET Hard Real-Time Requirement be Relaxed? -- Execution Time Model (Confidence Interval, Distribution)

– 99.9% of Deadlines are Met Given 99.9% Execution Time Confidence, Release Frequency, and Interference

• Service Negotiation & Execution Control - EPA/PCIP– Can Execution Parameter Changes Be Handled Maintaining

(Degrading) Deadline Confidences? -- Parametric Monitoring and Re-estimation of Confidences

– Can Application Modify Service On-Line? -- Dynamic Admission

RT EPA/PCIP Design Issues

• Required RT-EPA Kernel Interface– Required Kernel Features (POSIX 1003.4 not sufficient)

• Priority Preemptable Kernel-level Threads, Priority Inversion Control, VM Page Wiring, and Kernel-space Modules

• Simple Implementation in single-user RTOS (e.g. VxWorks)

• More complex Implementation in multi-user OS (e.g. Solaris) possible given required features

– Portable RT “Kernel-Ware” modules (trusted like driver code)

• EPA Service Negotiation Interface and Control– Soft and “Termination” Deadlines and Confidences (Computed)– Execution Time Models (Distribution Assumption or Free)– Output Hold (Buffering) for Isochrony– Parameter Change Confidence Re-estimation (C(i), T(i), D(i))– Confidence and Deadline Management (Preserve Negotiated Confidences,

Signal Inability to Maintain Negotiation)

RT EPA Interface Design

Application

Execution Performance Agent

SinkDevice

SourceDevice

system call

DeviceInterface

Pipe-StageFilter

DeviceInterface

kernel API

HW / SW Interface

Low Frequency Interaction(Parameter Initialization andModification)

High-FrequencyInteraction and Per-BlockProcessing

Robot Control

Execution Performance Agent

POS RELAY

SHOULDER WRIST ELBOWARM BASE

POS RELAY POS RELAY POS RELAY POS RELAY

5 DOF Robot RTEPA Application

RACEControl

Execution Performance Agent

68HC11

RAMPCONTROL

YAWCONTROL

RAMPRANGE

YAW

CAMERA 68HC11 DIGITALCOMPASS

RACE RTEPA Application

RT EPA Confidence-Based Scheduling

computationtime distribution

Chigh, Dterm

signaland abort

Rmin

bufferedresponse

best-case executionhold earlyresponse

resp

onse

uti

lity

resp

onse

dam

age

time

release starttime

latestdesired

response termination

Clow, Dsoft

signal

response failure: dropout degradation

desiredoptimalresponse

earliestdesired

response

earliestpossibleresponse

utilitycurve

WCET

Cexpected

contextswitch

overhead

Ropt

bufferedresponse

desiredresponse interval

Extended Deadline Monotonic Equations• 3 Basic Equations (sufficient but not necessary)

1) Clow and Chigh from distribution equation

2) EPA Deadline-monotonic admission test inequality given interference from current thread pool

3) Maximum Interference from current thread pool

See www-sgc.colorado.edu/people/siewerts for detailed example

• Termination deadline required for equations to work

• Pessimistic interference assumption (required for hard or mixed hard/soft real-time)– All interfering threads run to their termination deadline every

release

– Worst case interference

• Reliable interference assumption (for soft real-time only)– All interfering threads are assumed to run to high confidence Cexp

RT-EPA Interface• Pipeline task required inputs for admission

– Entry point function pointer; Fptr– Release source; ISR signal or interval timer RT POSIX signal– Expected release period; Texp– Expected periodic execution time; Cexp– Execution time model; <sample array> or <noraml dist >– Desired soft and hard termination deadlines; Dsoft and Dterm– Desired soft and hard deadline confidences; Conf-soft, Conf-hard– Output description and period; Dptr, size, Dest-addr, Tout

• Returns– Soft and hard deadline confidence (actual or maximum possible given

current thread pool)

• Monitors & Controls– Actual execution time– Actual release times– Missed soft and hard deadlines– Termination of threads at Dterm

RT-EPA Implementation and Evaluation

• Demonstration RT EPA Implemented as VxWorks Task– EPA spawns and controls tasks (internal or interrupt release)

– Provides message queue interface for service negotiation

– Modeled as hard real-time periodic itself

• RACE (Rail-guided, Air-powered, Control Experiment)– 2 68HC11 microcontrollers (navigation and propulsion), 3 PWM servos,

ultrasonic range finder, digital compass, and color CCD camera

• EPA Experiments– Continuous Media : Qcam CCD frame processing for range determination

(knowledge of range to 0.5 inches every second)

– Continuous Control : Ramp position keeping (Qcam range input, serial motor servo output), RACE yaw control (digital compass input, serial motor servo output)

• Expected Outcome– Demonstration of EPA Negotiation Interface for Multiple Active Pipelines (on-

line tradeoffs by application using EPA)

RACE RT-EPA Experiment Setup

RACE Vehicle Close-up

RACE Rail-guided Carriage

RACE Ramp Ascent

RACE Optical Target at Minimum Range

RACE Optical Target at Full Range

Summary

• Confidence-Based Scheduling (Extension of Deadline Montonic Equations) used for Hard-to-Soft RT execution control

• EPA Interface Between Applications and Kernel Thread Scheduler– Parametric Control of Kernel Threads through EPA (E.g. Terminated or

Allowed to Overrun Soft Deadline)

– Tradeoffs through EPA for Application with Multiple Pipelines (Lower Video Confidence for Higher Control Confidence)

• Previous Work on In-Kernel Pipelines– EPA/PCIP Extends In-Kernel Pipelines for Control, Service

Negotiation, and Confidence-Based Scheduling

– EPA Monitors Execution Time Models and Release Frequency For Changes (Confidence Re-estimation)