The Real-Time Execution Performance Agent
An Hard/Soft Real-Time Digital Control and Continuous Media
Experiment to Demonstrate Confidence-Based Scheduling
With The RT-EPA Execution Control Interface
Sam Siewert
siewerts@rodin.colorado.edu
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
Low Frequency Interaction
(Parameter Initialization and
Modification)
Application
system call
kernel API
Execution Performance Agent
High-Frequency
Interaction and Per-Block
Processing
Device
Interface
Pipe-Stage
Filter
Device
Interface
HW / SW
Interface
Source
Device
Sink
Device
5 DOF Robot RTEPA Application
Robot Control
Execution Performance Agent
ARM
POS
RELAY
SHOULDER
POS
RELAY
WRIST
POS
RELAY
ELBOW
POS
RELAY
BASE
POS
RELAY
RACE RTEPA Application
RACE
Control
Execution Performance Agent
RAMP
RANGE
CAMERA
RAMP
CONTROL
68HC11
YAW
CONTROL
68HC11
YAW
DIGITAL
COMPASS
RT EPA Confidence-Based Scheduling
earliest
possible
response
earliest
desired
response
desired
optimal
response
latest
desired
response
response utility
release start
time
termination
response failure:
dropout degradation
response damage
time
utility
curve
desired
response interval
WCET
Cexpected
d
context
switch
overhead
computation
time distribution
best-case execution
hold early
response
Rmin
buffered
response
Ropt
buffered
response
Clow , Dsoft
signal
Chigh , Dterm
signal
and abort
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 s>
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)