The Feasibility Analysis of Mixed-Criticality Systems Saravanan - - PowerPoint PPT Presentation

Motivation Open Problem Possible Solution Design Methodology

The Feasibility Analysis of Mixed-Criticality Systems

Saravanan Ramanathan, Xiaozhe Gu, Arvind Easwaran

Nanyang Technological University, Singapore

July 5, 2016

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Motivation Open Problem Possible Solution Design Methodology

Outline

1

Motivation

2

Open Problem

3

Possible Solution

4

Design Methodology

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Motivation Open Problem Possible Solution Design Methodology

Outline

1

Motivation

2

Open Problem

3

Possible Solution

4

Design Methodology

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Motivation Open Problem Possible Solution Design Methodology

Motivation

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Motivation Open Problem Possible Solution Design Methodology

Outline

1

Motivation

2

Open Problem

3

Possible Solution

4

Design Methodology

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Motivation Open Problem Possible Solution Design Methodology

The open problem

What is a tight feasibility bound for Mixed-Criticality (MC) task systems?

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Motivation Open Problem Possible Solution Design Methodology

Outline

1

Motivation

2

Open Problem

3

Possible Solution

4

Design Methodology

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Motivation Open Problem Possible Solution Design Methodology

Possible Solution

Mixed-Criticality System: Single-core / Multi-core scheduling Dual-criticality / Multi-Criticality system Periodic / Sporadic task model Implicit / Constrained deadline

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Motivation Open Problem Possible Solution Design Methodology

Possible Solution

Mixed-Criticality System: Single-core / Multi-core scheduling Dual-criticality / Multi-Criticality system Periodic / Sporadic task model Implicit / Constrained deadline

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Motivation Open Problem Possible Solution Design Methodology

Mixed-Criticality Task Model

Task Model: Implicit-deadline dual-criticality (namely LO and HI) periodic task system is being considered. τi = (Ti,χi,CL

i ,CH i ,Di)

Ti ∈ R+ is the period, χi ∈ {LO, HI} is the criticality level, CL

i and CH i

are the LO- and HI-criticality Worst-Case Execution Time (WCET) values respectively; we assume CL

i ≤ CH i

and, Di = Ti is the relative deadline.

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Motivation Open Problem Possible Solution Design Methodology

MC Feasibility Analysis

U H

H

U L

L + U L H

1 1 3/4 3/4 Necessary Condition Feasible region Sufficient Condition

System-level utilizations are defined as UL

L

def

=

τi∈τL uL i ,

UL

H

def

=

τi∈τH uL i and

UH

H

def

=

τi∈τH uH i

where, uL

i = CL i /Ti and uH i = CH i /Ti

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Motivation Open Problem Possible Solution Design Methodology

Outline

1

Motivation

2

Open Problem

3

Possible Solution

4

Design Methodology

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Motivation Open Problem Possible Solution Design Methodology

Design Methodology

Challenge: Determining the worst-case mode switch pattern

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Motivation Open Problem Possible Solution Design Methodology

Design Methodology

Challenge: Determining the worst-case mode switch pattern Solution: Fluid model Execution rate (θi) determines the mode switch instant (CL

i /θL i )

Non-MC systems: Most fluid algorithms are optimal

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Motivation Open Problem Possible Solution Design Methodology

Design Methodology

Design of optimal scheduling algorithm involves

1

In LO mode: Schedule LO-criticality tasks as late as possible

2

In LO mode: Schedule HI-criticality tasks with their virtual deadline (CL

i /θL i )

3

In HI mode: Optimal scheduling of HI-criticality tasks inclusive of carry-over demand of HI-criticality tasks.

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Motivation Open Problem Possible Solution Design Methodology

Design Methodology

HI-mode schedulability: In the absence of LO-tasks, fluid scheduling can optimally schedule HI-tasks in HI-mode.

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Motivation Open Problem Possible Solution Design Methodology

Design Methodology

HI-mode schedulability: In the absence of LO-tasks, fluid scheduling can optimally schedule HI-tasks in HI-mode. LO-mode schedulability:

1

Use DP-Fair to schedule HI-tasks in LO mode

Virtual deadline (CL

i /θL i ) and actual deadline (Ti)

2

Schedule LO-tasks as late as possible

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Motivation Open Problem Possible Solution Design Methodology

Thank you..! Questions..?

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