The Real-Time Execution Performance Agent Sam Siewert An Hard/Soft Real-Time Digital Control and Continuous Media Experiment 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 AperiodicBurstyPeriodic –Range of RT Performance Reliability Required Best-EffortConfidence-BasedGuaranteed 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 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 Sink Device Source Device system call Device Interface Pipe-Stage Filter Device Interface kernel API HW / SW Interface Low Frequency Interaction (Parameter Initialization and Modification) High-Frequency Interaction and Per-Block Processing

Robot Control Execution Performance Agent POS RELAY SHOULDER WRIST ELBOW ARMBASE POS RELAY POS RELAY POS RELAY POS RELAY 5 DOF Robot RTEPA Application

RACE Control Execution Performance Agent 68HC11 RAMP CONTROL YAW CONTROL RAMP RANGE YAW CAMERA 68HC11 DIGITAL COMPASS RACE RTEPA Application

RT EPA Confidence-Based Scheduling computation time distribution C high, D term signal and abort R min buffered response best-case execution hold early response response utility response damage time release start time latest desired response termination C low, D soft signal response failure: dropout degradation desired optimal response earliest desired response earliest possible response utility curve WCET C expected context switch overhead R opt buffered response desired response 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; or –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)