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ASIL-Decomposition Based Resource Allocation Optimization for Automotive E/E Architectures

Dorsa Zaheri, Hans-Christian Reuss

TL;DR

This work tackles the deployment problem for automotive E/E architectures under ISO 26262 safety constraints by formulating a single-step MILP that jointly performs ASIL decomposition and resource allocation. The method models software as a DAG of tasks with ASIL requirements and maps them to heterogeneous ECUs while enforcing reliability and interference constraints, including PMHF-based safety guarantees and memory limits. The contributions include a multi-objective optimization framework that minimizes development cost and maximum execution time, and a linearized reliability constraint enabling ILP solvers to find exact deployments. Experimental results on a four-ECU case show the method can achieve lower cost with acceptable latency or lower latency with reasonable cost, and comparative solver analysis demonstrates practical efficiency. The approach advances automated, safety-compliant deployment for SDV-era E/E architectures and lays groundwork for extending the MILP to routing and scheduling of inter-task messages.

Abstract

Recent years have brought a surge of efforts in rethinking the vehicle's electrical and/or electronic (E/E) architecture as well as the development process to reduce complexity and enable automation, connectivity, and electromobility. Resource allocation is an important step of the development process that can influence the quality of the designed system. As the design space is large and complex, intuitive design can turn into a time-consuming process with sub-optimal solutions. Here, we present an approach to automatically map software components to available hardware resources. Compared to existing frameworks, our method provides a wider range of safety analyses in compliance with the ISO 26262 standard, encompassing aspects such as reliability, task scheduling, and automotive safety integrity level (ASIL) compatibility. We propose an integer linear programming (ILP)-based approach to perform the ASIL decomposition technique specified by the standard. This technique proves beneficial when suitable hardware resources are unavailable for a safety-critical application. We formulate a multi-objective optimization problem to minimize both the development cost and the maximum execution times of critical function chains. The effectiveness of the proposed approach is investigated on an exemplary case study, and the results of the performance analysis are presented and discussed.

ASIL-Decomposition Based Resource Allocation Optimization for Automotive E/E Architectures

TL;DR

This work tackles the deployment problem for automotive E/E architectures under ISO 26262 safety constraints by formulating a single-step MILP that jointly performs ASIL decomposition and resource allocation. The method models software as a DAG of tasks with ASIL requirements and maps them to heterogeneous ECUs while enforcing reliability and interference constraints, including PMHF-based safety guarantees and memory limits. The contributions include a multi-objective optimization framework that minimizes development cost and maximum execution time, and a linearized reliability constraint enabling ILP solvers to find exact deployments. Experimental results on a four-ECU case show the method can achieve lower cost with acceptable latency or lower latency with reasonable cost, and comparative solver analysis demonstrates practical efficiency. The approach advances automated, safety-compliant deployment for SDV-era E/E architectures and lays groundwork for extending the MILP to routing and scheduling of inter-task messages.

Abstract

Recent years have brought a surge of efforts in rethinking the vehicle's electrical and/or electronic (E/E) architecture as well as the development process to reduce complexity and enable automation, connectivity, and electromobility. Resource allocation is an important step of the development process that can influence the quality of the designed system. As the design space is large and complex, intuitive design can turn into a time-consuming process with sub-optimal solutions. Here, we present an approach to automatically map software components to available hardware resources. Compared to existing frameworks, our method provides a wider range of safety analyses in compliance with the ISO 26262 standard, encompassing aspects such as reliability, task scheduling, and automotive safety integrity level (ASIL) compatibility. We propose an integer linear programming (ILP)-based approach to perform the ASIL decomposition technique specified by the standard. This technique proves beneficial when suitable hardware resources are unavailable for a safety-critical application. We formulate a multi-objective optimization problem to minimize both the development cost and the maximum execution times of critical function chains. The effectiveness of the proposed approach is investigated on an exemplary case study, and the results of the performance analysis are presented and discussed.
Paper Structure (11 sections, 23 equations, 4 figures, 6 tables)

This paper contains 11 sections, 23 equations, 4 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Methodology
  4. System Model
  5. Software Model
  6. Hardware Model
  7. ASIL Decomposition Model
  8. Reliability Calculation
  9. MILP Model Formulation
  10. Experimental Results
  11. Conclusion

Figures (4)

  • Figure 1: ASIL decomposition schemas in ISO 26262 ref24
  • Figure 2: The exemplary graph consisting of six tasks
  • Figure 3: Optimal deployment solutions for the case study with the primary objective: (a) minimization of the development cost and (b) minimization of the maximum execution time
  • Figure 4: Performance evaluation of the proposed approach. (a) Application on a topology consisting of four ECUs with ASIL C and ASIL B tasks, without ASIL decomposition. (b) Impact of ASIL decomposition on solving time. (c) Comparison of cost function results between the proposed ILP and GA methods.