Elastic Service Provision for Intelligent Vehicle Functions

Kugele, Stefan; Hettler, David; Shafaei, Sina

doi:10.1109/itsc.2018.8569374

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…The idea behind this selective concentration of computational resources (cf. [52]) is the attempt to gradually transform from a highly federated and distributed architecture into a centralised one. Still today, ECUs and their included software functions belong to logical domains such as infotainment, powertrain, chassis, and comfort.…”

Section: Automotive Framework Conditionsmentioning

confidence: 99%

Model-based resource analysis and synthesis of service-oriented automotive software architectures

2021

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Context Automotive software architectures describe distributed functionality by an interaction of software components. One drawback of today’s architectures is their strong integration into the onboard communication network based on predefined dependencies at design time. The idea is to reduce this rigid integration and technological dependencies. To this end, service-oriented architecture offers a suitable methodology since network communication is dynamically established at run-time. Aim We target to provide a methodology for analysing hardware resources and synthesising automotive service-oriented architectures based on platform-independent service models. Subsequently, we focus on transforming these models into a platform-specific architecture realisation process following AUTOSAR Adaptive. Approach For the platform-independent part, we apply the concepts of design space exploration and simulation to analyse and synthesise deployment configurations, i. e., mapping services to hardware resources at an early development stage. We refine these configurations to AUTOSAR Adaptive software architecture models representing the necessary input for a subsequent implementation process for the platform-specific part. Result We present deployment configurations that are optimal for the usage of a given set of computing resources currently under consideration for our next generation of E/E architecture. We also provide simulation results that demonstrate the ability of these configurations to meet the run time requirements. Both results helped us to decide whether a particular configuration can be implemented. As a possible software toolchain for this purpose, we finally provide a prototype. Conclusion The use of models and their analysis are proper means to get there, but the quality and speed of development must also be considered.

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Section: Automotive Framework Conditionsmentioning

confidence: 99%

Model-based resource analysis and synthesis of service-oriented automotive software architectures

2021

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“…For this phase, we have proposed the Orchestrator for controlling the integration of the software architecture in our previous work, as explained above. Other authors have proposed the use of machine learning for architecture controllers [13]. In this work we propose and explore a subsequent resource orchestration phase, where services selected during functional orchestration are mapped to the ECU cluster such that the resource and timing requirements of services are fulfilled, while the power consumption of the ECU cluster is reduced.…”

Section: Introductionmentioning

confidence: 99%

Optimization-based Resource Allocation for an Automotive Service-oriented Software Architecture

Kampmann

Luer

Kowalewski

et al. 2022

2022 IEEE Intelligent Vehicles Symposium (IV)

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This paper presents an approach for allocation of resources in an automotive service-oriented software architecture. Using mathematical optimization, we assign computational resources of an automotive compute cluster to a set of software services. Additionally, scheduling parameters of services are optimized under the consideration of dependencies between data flows and computations within services. The optimization minimizes power consumption and the maximum execution times of critical effect chains in a multi-objective optimization problem. The evaluation investigates the achievable reduction in power consumption using an exemplary system. Furthermore, we demonstrate a sharp reduction in maximum execution times of effect chains that span multiple services and ECUs.

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Toward a Resilient Automotive Service-Oriented Architecture by using Dynamic Orchestration

Schindewolf,

Grimm,

Lingor

et al. 2022

2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)

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Elastic Service Provision for Intelligent Vehicle Functions

Cited by 7 publications

References 13 publications

Model-based resource analysis and synthesis of service-oriented automotive software architectures

Model-based resource analysis and synthesis of service-oriented automotive software architectures

Optimization-based Resource Allocation for an Automotive Service-oriented Software Architecture

Toward a Resilient Automotive Service-Oriented Architecture by using Dynamic Orchestration

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