This article shows how restrictions of physical I/O
interfaces in terms of grouping, dual-power, and connector
segregation are considered correctly in the combinatorial
optimization of avionics architectures like large Integrated
Modular Avionics (IMA) systems. For each of the I/O sharing
restrictions a constraint formulation for multi-objective Integer
Linear Programing (ILP) is developed. The novel constraints are
applied for task assignment optimization in a verification example
and a real-world example of 536 tasks. Verification shows that the
I/O sharing is handled correctly and the real-world application
proofs the method to be industrially applicable. Moreover, the
influence on the solving speed is investigated. I/O restrictions can
rise the optimization time by factor 10, but the loss of the
optimization potential is below 10% for the tested objectives and
examples.
%0 Book
%1 annighoefer2018b
%A Annighoefer, Bjoern
%B 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)
%D 2018
%K imported myown
%T Enabling correct I/O sharing in the combinatorial optimization of large avionics systems
%X This article shows how restrictions of physical I/O
interfaces in terms of grouping, dual-power, and connector
segregation are considered correctly in the combinatorial
optimization of avionics architectures like large Integrated
Modular Avionics (IMA) systems. For each of the I/O sharing
restrictions a constraint formulation for multi-objective Integer
Linear Programing (ILP) is developed. The novel constraints are
applied for task assignment optimization in a verification example
and a real-world example of 536 tasks. Verification shows that the
I/O sharing is handled correctly and the real-world application
proofs the method to be industrially applicable. Moreover, the
influence on the solving speed is investigated. I/O restrictions can
rise the optimization time by factor 10, but the loss of the
optimization potential is below 10% for the tested objectives and
examples.
@book{annighoefer2018b,
__markedentry = {[Annighoefer:3]},
abstract = {This article shows how restrictions of physical I/O
interfaces in terms of grouping, dual-power, and connector
segregation are considered correctly in the combinatorial
optimization of avionics architectures like large Integrated
Modular Avionics (IMA) systems. For each of the I/O sharing
restrictions a constraint formulation for multi-objective Integer
Linear Programing (ILP) is developed. The novel constraints are
applied for task assignment optimization in a verification example
and a real-world example of 536 tasks. Verification shows that the
I/O sharing is handled correctly and the real-world application
proofs the method to be industrially applicable. Moreover, the
influence on the solving speed is investigated. I/O restrictions can
rise the optimization time by factor 10, but the loss of the
optimization potential is below 10% for the tested objectives and
examples.},
added-at = {2019-02-28T16:45:14.000+0100},
author = {Annighoefer, Bjoern},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2b57ea0f01c9c725fc2e3ae7f80cc4e3a/annighoefer},
booktitle = {2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)},
file = {:Annighoefer - EnablingCorrectIoSharingInTheCombinatorial OptimizationOfLargeAvionicsSystems_Dasc2018.pdf:PDF},
interhash = {e23dd2fb32d4f2a2fa33255da49cab9e},
intrahash = {b57ea0f01c9c725fc2e3ae7f80cc4e3a},
keywords = {imported myown},
timestamp = {2020-01-27T08:47:31.000+0100},
title = {Enabling correct I/O sharing in the combinatorial optimization of large avionics systems},
year = 2018
}