Functional size measurement for processor load estimation hassan soubra

FUNCTIONAL SIZE MEASUREMENT FOR PROCESSOR LOAD ESTIMATION IN AUTOSAR

Hassan Soubra, Alain Abran, Mehdi Sehit

Agenda Introduction

Research Issue

Litterature review

Overviews of COSMIC, AUTOSAR and SYMTA/S

Experimental Set-up

Results

Conclusions

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3

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2 Soubra 2015 -‐-‐ all rights reserved

Introduction

•  Software functional size is a key input for building software development estimation models, effort models, benchmark models, and quality models

•  It can also be used for purposes such as processor load estimation, network traffic estimation and acceptance condition estimation

•  Context: Autosar


Litterature review

COSMIC based guideline and procedure for

AUTOSAR

Prediction and verification of

timing constraints of

embedded software

Procedure and tool for

Simulink

Basic timing model to allow application of such timing interfaces

Procedure and tool for UML

Code Size Optimizing

memory requirements respects real-

time schedulability

constraints

Load balancing mechanisms for efficient utilization of

CPU



COSMIC

measures the Func@onal User Requirements (FUR) of soGware. Func@onal size measured by COSMIC is

designed to be independent of any implementa@on

decisions embedded in the opera@onal ar@facts of the

soGware.

AUTOSAR

provides a set of concepts and a methodology for

design and implementa@on of automo@ve E/E systems. AUTOSAR methodology follows a model-‐driven

approach

SYMTA/S

Models and analyzes real-‐@me embedded systems in order to measure system performance (e.g. Worst

Case Execu@on @me -‐WCET, CPU load, end to end

latencies, etc.) while taking into account various

scheduling constraints and differing execu@on scenarios.




Experimental Set-up

Architecture Number of ECUs in the architecture

Total Number of AUTOSAR models used in

the architecture

Total Number of Runnables used in the

architecture

A 1 107 107B 2 12 24C 3 5 15D 4 21 84E 5 7 35F 6 11 66G 7 1 7Total number used in all

architectures 164 338


Approach

We used linear regression analysis to build es@ma@on models of ECU processor load for AUTOSAR models.

Correlate the rela@on between ECU processor load and COSMIC func@onal size ()

from steps 1 &2

Observe the processor load

In the AUTOSAR model developed using SYMTA/S, run from 0% (free) to 100% (fully occupied).

Measure the func@onal size of an input AUTOSAR model

AGer its alloca@on to one of the seven architectures. To speed up the measurement process and reduce the possibility of human error, we used an automated prototype tool developed in our study.


Automation Tool


Automation Tool


Results


Linear regression to estimate processor load

The mean difference between the actual data and the es@mated data for the 24 models is 10.59 %. The accuracy of the es@mates is approximately 90%.


Conclusion

•  A study of the relationship between FSM and processor load, in AUTOSAR.

•  The findings have demonstrated the dependence of ECU processor load on COSMIC functional size.

•  Automation prototype tool. •  24 models were used to verify the accuracy of the

estimates produced by our automated approach.


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