C-PO: A Context-Based Application-Placement Optimization for Autonomous Vehicles
Tobias Kain1,a, Hans Tompits2, Timo Frederik Horeis3,a, Johannes Heinrich3,b, Julian-Steffen Müller1,b, Fabian Plinkez3,c, Hendrik Decke1,c and Marcel Aguirre Mehlhorn1,d
1Volkswagen AG, Wolfsburg, Germany
atobias.kain@volkswagen.de
bjulian-steffen.mueller@volkswagen.de
chendrik.decke@volkswagen.de
dmarcel.aguirre.mehlhorn@volkswagen.de
2Technische Universität Wien, Vienna, Austria
tompits@kr.tuwien.ac.at
3IQZ GmbH, Hamburg, Germany
ahoreis@iqz-wuppertal.de
bheinrich@iqz-wuppertal.de
cplink@iqz-wuppertal.de
ABSTRACT
Autonomous vehicles are complex distributed systems consisting of multiple software applications and computing nodes. Determining the assignment between these software applications and computing nodes is known as the application-placement problem. The input of this problem is a set of applications, their requirements, a set of computing nodes, and their provided resources. Due to the potentially large solution space of the problem, an optimization goal defines which solution is desired the most. However, the optimization goal used for the applicationplacement problem is not static but has to be adapted according to the current context the vehicle is experiencing. Therefore, an approach for a context-based determination of the optimization goal for a given instance of an application-placement problem is required. In this paper, we introduce C-PO, an approach to address this issue. C-PO ensures that if the safety level of a system drops due to an occurring failure, the optimization goal for the successively executed application-placement determination aims to restore the safety level. Once the highest safety level is reached, C-PO optimizes the application placement according to the current driving situation. Furthermore, we introduce two methods for dynamically determining the required level of safety.
Keywords: Autonomous Driving, Application-Placement Problem, Context-Based Optimization.
